anchor.diff:  Preliminary results indicate a broad spectrum of yet to be explored options.
   As the PhD is still in an early phase, we hope to narrow the scope in the next months,
   based on feedback of the doctoral consortium."
  -journal_saleem_6,6,"Muhammad Saleem,  Yasar Khan,  Ali Hasnain,  Ivan Ermilov and Axel-Cyrille Ngonga Ngomo",saleem,A Fine-Grained Evaluation of SPARQL Endpoint Federation Systems,journal,Querying/SPARQL (I),4,Muhammad Saleem,http://www.semantic-web-journal.net/content/fine-grained-evaluation-sparql-endpoint-federation-systems-2,501,2016-10-20T10:30:00,2016-10-20T11:50:00,"The Web of Data has grown enormously over the last years. Currently, it comprises a large compendium of interlinked and distributed datasets from multiple domains. Running complex queries on this compendium often requires accessing data from different endpoints within one query. The abundance of datasets and the need for running complex query has thus motivated a considerable body of work on SPARQL query federation systems, the dedicated means to access data distributed over the Web of Data. However, the granularity of previous evaluations of such systems has not allowed deriving of insights concerning their behavior in different steps involved during federated query processing. In this work, we perform extensive experiments to compare state-of-the-art SPARQL endpoint federation systems using the comprehensive performance evaluation framework FedBench. In addition to considering the tradition query runtime as an evaluation criterion, we extend the scope of our performance evaluation by considering criteria, which have not been paid much attention to in previous studies. In particular, we consider the number of sources selected, the total number of SPARQL ASK requests used, the completeness of answers as well as the source selection time. Yet, we show that they have a significant impact on the overall query runtime of existing systems. Moreover, we extend FedBench to mirror a highly distributed data environment and assess the behavior of existing systems by using the same performance criteria. As the result we provide a detailed analysis of the experimental outcomes that reveal novel insights for improving current and future SPARQL federation systems."
  -journal_nuzzolese_1,1,"Andrea Giovanni Nuzzolese, Valentina Presutti, Aldo Gangemi, Silvio Peroni and Paolo Ciancarini",nuzzolese,Aemoo: Linked Data exploration based on Knowledge Patterns,journal,Search (II),3,Andrea Giovanni Nuzzolese,http://dx.doi.org/10.1016/j.websem.2015.12.001,504+505,2016-10-20T15:30:00,2016-10-20T16:50:00,"This paper presents a novel approach to Linked Data exploration that uses Encyclopedic Knowledge Patterns (EKPs) as relevance criteria for selecting, organising, and visualising knowledge. EKP are discovered by mining the linking structure of Wikipedia and evaluated by means of a user-based study, which shows that they are cognitively sound as models for building entity summarisations. We implemented a tool named Aemoo that supports EKP-driven knowledge exploration and integrates data coming from heterogeneous resources, namely static and dynamic knowledge as well as text and Linked Data. Aemoo is evaluated by means of controlled, task-driven user experiments in order to assess its usability, and ability to provide relevant and serendipitous information as compared to two existing tools: Google and RelFinder."
  -journal_mazumdar_2,2,"Suvodeep Mazumdar, Daniela Petrelli,  Khadija Elbedweihy,  Vitaveska Lanfranchi and Fabio Ciravegna",mazumdar,Affective Graphs: The Visual Appeal of Linked Data,journal,Interaction,4,Suvodeep Mazumdar,http://www.semantic-web-journal.net/content/affective-graphs-visual-appeal-linked-data,504+505,2016-10-19T11:00:00,2016-10-19T12:20:00,"The essence and value of Linked Data lies in the ability of humans and machines to query, access and reason upon highly structured and formalised data. Ontology structures provide an unambiguous description of the structure and content of data. While a multitude of software applications and visualization systems have been developed over the past years for Linked Data, there is still a significant gap that exists between applications that consume Linked Data and interfaces that have been designed with significant focus on aesthetics. Though the importance of aesthetics in affecting the usability, effectiveness and acceptability of user interfaces have long been recognised, little or no explicit attention has been paid to the aesthetics of Linked Data applications. In this paper, we introduce a formalised approach to developing aesthetically pleasing semantic web interfaces by following aesthetic principles and guidelines identified from literature. We apply such principles to design and develop a generic approach of using visualizations to support exploration of Linked Data, in an interface that is pleasing to users. This provides users with means to browse ontology structures, enriched with statistics of the underlying data, facilitating exploratory activities and enabling visual query for highly precise information needs. We evaluated our approach in three ways: an initial objective evaluation comparing our approach with other well-known interfaces for the semantic web and two user evaluations with semantic web researchers."
  -journal_rospocher_8,8,"Marco Rospocher, Marieke van Erp, Piek Vossen, Antske Fokkens, Itziar Aldabe, German Rigau, Aitor Soroa, Thomas Ploeger and Tessel Bogaard",rospocher,Building event-centric knowledge graphs from news,journal,Natural Language Processing,4,Marco Rospocher,http://dx.doi.org/10.1016/j.websem.2015.12.004,504+505,2016-10-21T10:30:00,2016-10-21T11:50:00,"Knowledge graphs have gained increasing popularity in the past couple of years, thanks to their adoption in everyday search engines. Typically, they consist of fairly static and encyclopedic facts about persons and organizations–e.g. a celebrity’s birth date, occupation and family members–obtained from large repositories such as Freebase or Wikipedia. In this paper, we present a method and tools to automatically build knowledge graphs from news articles. As news articles describe changes in the world through the events they report, we present an approach to create Event-Centric Knowledge Graphs (ECKGs) using state-of-the-art natural language processing and semantic web techniques. Such ECKGs capture long-term developments and histories on hundreds of thousands of entities and are complementary to the static encyclopedic information in traditional knowledge graphs. We describe our event-centric representation schema, the challenges in extracting event information from news, our open source pipeline, and the knowledge graphs we have extracted from four different news corpora: general news (Wikinews), the FIFA world cup, the Global Automotive Industry, and Airbus A380 airplanes. Furthermore, we present an assessment on the accuracy of the pipeline in extracting the triples of the knowledge graphs. Moreover, through an event-centered browser and visualization tool we show how approaching information from news in an event-centric manner can increase the user’s understanding of the domain, facilitates the reconstruction of news story lines, and enable to perform exploratory investigation of news hidden facts."""
  -journal_gerber_11,11,"Daniel Gerber, Diego Esteves, Jens Lehmann, Lorenz Bühmann, Ricardo Usbeck, Axel-Cyrille Ngonga Ngomo and René Speck",gerber,DeFacto - Temporal and multilingual Deep Fact Validation,journal,Knowledge Graphs,3,Daniel Gerber,http://dx.doi.org/10.1016/j.websem.2015.08.001,501,2016-10-19T11:00:00,2016-10-19T12:20:00,"One of the main tasks when creating and maintaining knowledge bases is to validate facts and provide sources for them in order to ensure correctness and traceability of the provided knowledge. So far, this task is often addressed by human curators in a three-step process: issuing appropriate keyword queries for the statement to check using standard search engines, retrieving potentially relevant documents and screening those documents for relevant content. The drawbacks of this process are manifold. Most importantly, it is very time-consuming as the experts have to carry out several search processes and must often read several documents. In this article, we present DeFacto (Deep Fact Validation)—an algorithm able to validate facts by finding trustworthy sources for them on the Web. DeFacto aims to provide an effective way of validating facts by supplying the user with relevant excerpts of web pages as well as useful additional information including a score for the confidence DeFacto has in the correctness of the input fact. To achieve this goal, DeFacto collects and combines evidence from web pages written in several languages. In addition, DeFacto provides support for facts with a temporal scope, i.e., it can estimate in which time frame a fact was valid. Given that the automatic evaluation of facts has not been paid much attention to so far, generic benchmarks for evaluating these frameworks were not previously available. We thus also present a generic evaluation framework for fact checking and make it publicly available."
  -journal_mccrae_7,7,"John P. McCrae, Mihael Arcan, Kartik Asooja, Jorge Gracia, Paul Buitelaar and Philipp Cimiano",mccrae,Domain Adaptation for Ontology Localization,journal,Multilinguality,4,John P. McCrae,http://dx.doi.org/10.1016/j.websem.2015.12.001,501,2016-10-19T14:00:00,2016-10-19T15:20:00,"Ontology localization is the task of adapting an ontology to a different cultural context, and has been identified as an important task in the context of the Multilingual Semantic Web vision. The key task in ontology localization is translating the lexical layer of an ontology, i.e., its labels, into some foreign language. For this task, we hypothesize that the translation quality can be improved by adapting a machine translation system to the domain of the ontology. To this end, we build on the success of existing statistical machine translation (SMT) approaches, and investigate the impact of different domain adaptation techniques on the task. In particular, we investigate three techniques: (i) enriching a phrase table by domain-specific translation candidates acquired from existing Web resources, (ii) relying on Explicit Semantic Analysis as an additional technique for scoring a certain translation of a given source phrase, as well as (iii) adaptation of the language model by means of weighting n-grams with scores obtained from topic modelling. We present in detail the impact of each of these three techniques on the task of translating ontology labels. We show that these techniques have a generally positive effect on the quality of translation of the ontology and that, in combination, they provide a significant improvement in quality. "
  -journal_arenas_12,12,"Marcelo Arenas, Bernardo Cuenca Grau, Evgeny Kharlamov, Šarūnas Marciuška and Dmitriy Zheleznyakov",arenas,Faceted search over RDF-based knowledge graphs,journal,Search (II),2,Marcelo Arenas,http://dx.doi.org/10.1016/j.websem.2015.12.002,504+505,2016-10-20T15:30:00,2016-10-20T16:50:00,"Knowledge graphs such as Yago and Freebase have become a powerful asset for enhancing search, and are being intensively used in both academia and industry. Many existing knowledge graphs are either available as Linked Open Data, or they can be exported as RDF datasets enhanced with background knowledge in the form of an OWL 2 ontology. Faceted search is the de facto approach for exploratory search in many online applications, and has been recently proposed as a suitable paradigm for querying RDF repositories. In this paper, we provide rigorous theoretical underpinnings for faceted search in the context of RDF-based knowledge graphs enhanced with OWL 2 ontologies. We identify well-defined fragments of SPARQL that can be naturally captured using faceted search as a query paradigm, and establish the computational complexity of answering such queries. We also study the problem of updating faceted interfaces, which is critical for guiding users in the formulation of meaningful queries during exploratory search. We have implemented our approach in a fully-fledged faceted search system, SemFacet, which we have evaluated over the Yago knowledge graph."
  -journal_vandenbussche_3,3,"Pierre-Yves Vandenbussche, Ghislain A. Atemezing, Maria Poveda and Bernard Vatant",vandenbussche,Linked Open Vocabularies (LOV): a gateway to reusable semantic vocabularies on the Web,journal,Ontologies (I),1,Pierre-Yves Vandenbussche,http://www.semantic-web-journal.net/content/linked-open-vocabularies-lov-gateway-reusable-semantic-vocabularies-web-1,501,2016-10-20T15:30:00,2016-10-20T16:50:00,"One of the major barriers to the deployment of Linked Data is the difficulty that data publishers have in determining which vocabularies to use to describe the semantics of data. This system report describes Linked Open Vocabularies (LOV), a high quality catalogue of reusable vocabularies for the description of data on the Web. The LOV initiative gathers and makes visible indicators that have not been previously harvested such as the interconnections between vocabularies, version history along with past and current referent (individual or organization). The report details the various components of the system along with some innovations such as the introduction of a property-level boost in the vocabulary search scoring which takes into account the property's type (e.g rdfs:label, dc:comment) associated with a matching literal value. By providing an extensive range of data access methods (full-text search, SPARQL endpoint, API, data dump or UI), the project aims at facilitating the reuse of well-documented vocabularies in the Linked Data ecosystem. The adoption of LOV by many applications and methods shows the importance of such a set of vocabularies and related features for the ontology design activity and the publication of data on the Web."
  -journal_calvanese_4,4,"Diego Calvanese, Benjamin Cogrel, Sarah Komla-Ebri, Roman Kontchakov, Davide Lanti, Martin Rezk, Mariano Rodriguez-Muro and Guohui Xiao",calvanese,Ontop: Answering SPARQL queries over relational databases,journal,Querying/SPARQL (II),3,Diego Calvanese,http://www.semantic-web-journal.net/content/ontop-answering-sparql-queries-over-relational-databases-1,502,2016-10-21T13:30:00,2016-10-21T14:50:00,"We present Ontop, an open-source Ontology-Based Data Access (OBDA) system that allows for querying relational data sources through a conceptual representation of the domain of interest, provided in terms of an ontology, to which the data sources are mapped. Key features of Ontop are its solid theoretical foundations, a virtual approach to OBDA, which avoids materializing triples and is implemented through the query rewriting technique, extensive optimizations exploiting all elements of the OBDA architecture, its compliance to all relevant W3C recommendations (including SPARQL queries, R2RML mappings, and OWL 2 QL and RDFS ontologies), and its support for all major relational databases."
  -journal_lephuoc_9,9,Danh Le-Phuoc,lephuoc,Operator-aware approach for boosting performance in RDF stream processing,journal,Streams,3,Danh Le-Phuoc,http://dx.doi.org/10.1016/j.websem.2016.04.001,501,2016-10-20T13:30:00,2016-10-20T14:50:00,"To enable efficiency in stream processing, the evaluation of a query is usually performed over bounded parts of (potentially) unbounded streams, i.e., processing windows “slide” over the streams. To avoid inefficient re-evaluations of already evaluated parts of a stream in respect to a query, incremental evaluation strategies are applied, i.e., the query results are obtained incrementally from the result set of the preceding processing state without having to re-evaluate all input buffers. This method is highly efficient but it comes at the cost of having to maintain processing state, which is not trivial, and may defeat performance advantages of the incremental evaluation strategy. In the context of RDF streams the problem is further aggravated by the hard-to-predict evolution of the structure of RDF graphs over time and the application of sub-optimal implementation approaches, e.g., using relational technologies for storing data and processing states which incur significant performance drawbacks for graph-based query patterns. To address these performance problems, this paper proposes a set of novel operator-aware data structures coupled with incremental evaluation algorithms which outperform the counterparts of relational stream processing systems. This claim is demonstrated through extensive experimental results on both simulated and real datasets."
  -journal_zaveri_5,5,"Amrapali Zaveri, Anisa Rula, Andrea Maurino, Ricardo Pietrobon, Jens Lehmann and Sören Auer",zaveri,Quality Assessment for Linked Data: A Survey,journal,Linked Data Measurement,4,Amrapali Zaveri,http://www.semantic-web-journal.net/content/quality-assessment-linked-data-survey,504+505,2016-10-20T13:30:00,2016-10-20T14:50:00,"The development and standardization of semantic web technologies has resulted in an unprecedented volume of data being published on the Web as Linked Data (LD). However, we observe widely varying data quality ranging from extensively curated datasets to crowdsourced and extracted data of relatively low quality. In this article, we present the results of a systematic review of approaches for assessing the quality of LD. We gather existing approaches and analyze them qualitatively. In particular, we unify and formalize commonly used terminologies across papers related to data quality and provide a comprehensive list of 18 quality dimensions and 69 metrics. Additionally, we qualitatively analyze the 30 core approaches and 12 tools using a set of attributes. The aim of this article is to provide researchers and data curators a comprehensive understanding of existing work, thereby encouraging further experimentation and development of new approaches focused towards data quality, specifically for LD."
  -journal_vegagorgojo_10,10,"Guillermo Vega-Gorgojo, Laura Slaughter, Martin Giese, Simen Heggestøyl, Ahmet Soylu and Arild Waaler",vegagorgojo,Visual query interfaces for semantic datasets: an evaluation study,journal,Interaction,3,Guillermo Vega-Gorgojo,http://dx.doi.org/10.1016/j.websem.2016.01.002,504+505,2016-10-19T11:00:00,2016-10-19T12:20:00,"The rapid growth of the Linked Open Data cloud, as well as the increasing ability to lift relational enterprise datasets to a semantic, ontology-based level means that vast amounts of information are now available in a representation that closely matches the conceptualizations of the potential users of this information. This makes it interesting to create ontology based, user-oriented tools for searching and exploring this data. Although initial efforts were intended for tech users with knowledge of SPARQL/RDF, there are ongoing proposals designed for lay users. One of the most promising approaches is to use visual query interfaces, but more user studies are needed to assess their effectiveness. In this paper, we compare the effect on usability of two important paradigms for ontology-based query interfaces: form-based and graph-based interfaces. In order to reduce the number of variables affecting the comparison, we performed a user study with two state-of-the-art query tools developed by ourselves, sharing a large part of the code base: the graph-based tool OptiqueVQS*, and the form-based tool PepeSearch. We evaluated these tools in a formal comparison study with 15 participants searching a Linked Open Data version of the Norwegian Company Registry. Participants had to respond to 6 non-trivial search tasks using alternately OptiqueVQS* and PepeSearch. Even without previous training, retrieval performance and user confidence were very high, thus suggesting that both interface designs are effective for searching RDF datasets. Expert searchers had a clear preference for the graph-based interface, and mainstream searchers obtained better performance and confidence with the form-based interface. While a number of participants spontaneously praised the capability of the graph interface for composing complex queries, our results evidence that graph interfaces are difficult to grasp. In contrast, form interfaces are more learnable and relieve problems with disorientation for mainstream users. We have also observed positive results introducing faceted search and dynamic term suggestion in semantic search interfaces."
  -poster_takatsuki_10,10,"Terue Takatsuki, Mikako Saito, Sadahiro Kumagai, Eiki Takayama, Kazuya Ohshima, Nozomu Ohshiro, Kai Lenz, Nobuhiko Tanaka, Norio Kobayashi and Hiroshi Masuya",takatsuki,A RDF based Portal of Biological Phenotype Data produced in Japan,poster,Poster,25,Terue Takatsuki,paper10.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_yu_70,70,"Ran Yu, Besnik Fetahu, Ujwal Gadiraju and Stefan Dietze",yu,A Survey on Challenges in Web Markup Data for Entity Retrieval,poster,Poster,54,Ran Yu,paper70.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_yoon_85,85,"Seungjun Yoon, Sejin Chun, Xiongnan Jin and Kyong-Ho Lee",yoon,A Unified Interface for Optimizing Continuous Query in Heterogeneous RDF Stream Processing Systems,poster,Poster,50,Seungjun Yoon,paper85.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_sungmin_31,31,"Joo Sungmin, Seiji Koide, Hideaki Takeda, Daisuke Horyu, Akane Takezaki and Tomokazu Yoshida",sungmin,Agriculture Activity Ontology : An ontology for core vocabulary of agriculture activity,poster,Poster,21,Joo Sungmin,paper31.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_lanti_82,82,"Davide Lanti, Guohui Xiao and Diego Calvanese",lanti,An Evaluation of VIG with the BSBM Benchmark,poster,Poster,52,Davide Lanti,paper82.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_zhao_44,44,"Lihua Zhao, Naoya Arakawa, Hiroaki Wagatsuma and Ryutaro Ichise",zhao,An Ontology based Map Converter for Intelligent Vehicles,poster,Poster,03,Lihua Zhao,paper44.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_ren_43,43,"Xiangnan Ren, Olivier Curé, Houda Khrouf, Zakia Kazi-Aoul and Yousra Chabchoub",ren,Apache Spark and Apache Kafka at the rescue of distributed RDF Stream Processing engines,poster,Poster,48,Xiangnan Ren,paper43.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_mei_8,8,"Jing Mei, Wen Sun, Jing Li, Haifeng Liu, Xiang Li, Yiqin Yu and Guotong Xie",mei,Building Evidence Graph for Clinical Decision Support,poster,Poster,26,Jing Mei,paper8.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_urakawa_15,15,"Makoto Urakawa, Masaru Miyazaki, Hiroshi Fujisawa, Masahide Naemura and Ichiro Yamada",urakawa,Constructing Curriculum Ontology and Dynamic Learning Path Based on Resource Description Framework,poster,Poster,44,Makoto Urakawa,paper15.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_takaai_94,94,Motoyuki Takaai and Yohei Yamane,takaai,Constructing Semantic Networks of Development Activities from Weekly Reports,poster,Poster,16,Motoyuki Takaai ,paper94.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_song_90,90,"Yuting Song, Taisuke Kimura, Biligsaikhan Batjargal and Akira Maeda",song,Cross-Language Record Linkage using Word Embedding driven Metadata Similarity Measurement,poster,Poster,14,Yuting Song,paper90.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_yamaguchi_95,95,"Atsuko Yamaguchi, Kouji Kozaki, Kai Lenz, Yasunori Yamamoto, Hiroshi Masuya and Norio Kobayashi",yamaguchi,Data Acquisition by Traversing Class-Class Relationships over the Linked Open Data,poster,Poster,22,Atsuko Yamaguchi,paper95.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_agtrickauer_104,104,"Henning Agt-Rickauer, Jörg Waitelonis, Tabea Tietz and Harald Sack",agtrickauer,Data Integration for the Media Value Chain,poster,Poster,10,Henning Agt-Rickauer,paper104.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_fang_107,107,"Lu Fang, Qingliang Miao and Yao Meng",fang,DBpedia Entity Type Inference Using Categories,poster,Poster,42,Lu Fang,paper107.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_kume_93,93,"Satoshi Kume, Hiroshi Masuya, Yosky Kataoka and Norio Kobayashi",kume,Development of an Ontology for an Integrated Image Analysis Platform to enable Global Sharing of Microscopy Imaging Data,poster,Poster,23,Satoshi Kume,paper93.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_demeester_110,110,"Ben De Meester, Anastasia Dimou, Ruben Verborgh and Erik Mannens",demeester,Discovering and Using Functions via Content Negotiation,poster,Poster,41,Ben De Meester,paper110.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_solanki_19,19,"Monika Solanki, Bojan Bozic, Markus Freudenberg, Dimitris Kontokostas, Rob Brennan and Christian Dirschl",solanki,Enabling combined software and data engineering: the ALIGNED suite of ontologies,poster,Poster,45,Monika Solanki,paper19.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_liu_53,53,"Zhihui Liu, Weimin Ge, Xiaowang Zhang and Zhiyong Feng",liu,Enhancing Rule-based OWL Reasoning on Spark,poster,Poster,37,Zhihui Liu,paper53.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_martin_72,72,Peter Patel-Schneider and David Martin,martin,EXISTStential Aspects of SPARQL,poster,Poster,28,Peter Patel-Schneider ,paper72.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_mirza_4,4,"Paramita Mirza, Simon Razniewski and Werner Nutt",mirza,"Expanding Wikidata's Parenthood Information by 178%, or How To Mine Relation Cardinality Information",poster,Poster,18,Paramita Mirza,paper4.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_nuzzolese_56,56,"Andrea Giovanni Nuzzolese, Anna Lisa Gentile, Valentina Presutti and Aldo Gangemi",nuzzolese,Generating Conference Linked Open Data in One Click,poster,Poster,19,Andrea Giovanni Nuzzolese,paper56.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_fionda_67,67,"Valeria Fionda, Melisachew Wudage Chekol and Giuseppe Pirrò",fionda,Gize: A Time Warp in the Web of Data,poster,Poster,43,Valeria Fionda,paper67.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_rinciog_76,76,Octavian Rinciog and Vlad Posea,rinciog,GovLOD: Towards to a Linked Open Data Portal,poster,Poster,04,Octavian Rinciog ,paper76.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_basharat_96,96,"Amna Basharat, Khaled Rasheed and I. Budak Arpinar",basharat,Harnessing Crowds and Experts for Semantic Annotation of the Qur'an,poster,Poster,31,Amna Basharat,paper96.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_pareti_28,28,Paolo Pareti,pareti,Human-Machine Collaboration over Linked Data,poster,Poster,02,Paolo Pareti,paper28.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_morita_106,106,"Takeshi Morita, Yu Sugawara, Ryota Nishimura and Takahira Yamaguchi",morita,Implementing Customer Reception Service in Robot Cafe using Stream Reasoning and ROS based on PRINTEPS,poster,Poster,08,Takeshi Morita,paper106.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_wilmering_60,60,Thomas Wilmering and Mark B. Sandler,wilmering,Interdisciplinary Classification of Audio Effects in the Audio Effect Ontology,poster,Poster,47,Thomas Wilmering ,paper60.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_zhang_40,40,"Junzhao Zhang, Bingyi Zhang, Xiaowang Zhang and Zhiyong Feng",zhang,IRSMG: Accelerating Inexact RDF Subgraph Matching on the GPU,poster,Poster,34,Junzhao Zhang,paper40.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_peroni_86,86,"Silvio Peroni, David Shotton and Fabio Vitali",peroni,Jailbreaking your reference lists: the OpenCitations project strikes again,poster,Poster,30,Silvio Peroni,paper86.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_mccrae_23,23,John P. McCrae and Philipp Cimiano,mccrae,"LIXR: Quick, succinct conversion of XML to RDF",poster,Poster,55,John P. McCrae ,paper23.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_seydoux_101,101,"Nicolas Seydoux, Khalil Drira, Nathalie Hernandez and Thierry Monteil",seydoux,Lowering knowledge : Making constrained devices semantically interoperable,poster,Poster,06,Nicolas Seydoux,paper101.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_gandon_41,41,"Fabien Gandon, Raphaël Boyer, Olivier Corby and Alexandre Monnin",gandon,Materializing the editing history of Wikipedia as linked Data in DBpedia,poster,Poster,17,Fabien Gandon,paper41.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_saif_66,66,"Hassan Saif, Miriam Fernandez, Matthew Rowe and Harith Alani",saif,On the Role of Semantics for Detecting pro-ISIS Stances on Social Media,poster,Poster,32,Hassan Saif,paper66.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_harrow_57,57,"Ian Harrow, Martin Romacker, Andrea Splendiani, Stefan Negru, Peter Woollard, Scott Markel, Yasmin Alam-Faruque, Martin Koch, Erfan Younesi, James Malone and Ernesto Jimenez-Ruiz",harrow,Ontologies Guidelines for Best Practice and a Process to Evaluate Existing Ontologies Mapping Tools and Algorithms,poster,Poster,46,Ian Harrow,paper57.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_subercaze_50,50,Julien Subercaze and Christophe Gravier,subercaze,Parallel sort-merge-join reasoning,poster,Poster,39,Julien Subercaze ,paper50.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_ongenae_100,100,"Femke Ongenae, Femke De Backere, Jelle Nelis, Stijn De Pestel, Christof Mahieu, Shirley Elprama, Charlotte Jewell, An Jacobs, Pieter Simoens and Filip De Turck",ongenae,Personalized robot interactions to intercept behavioral disturbances of people with dementia,poster,Poster,07,Femke Ongenae,paper100.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_chun_49,49,"Sejin Chun, Jooik Jung, Xiongnan Jin, Seungjun Yoon and Kyong-Ho Lee",chun,Proactive Replication of Dynamic Linked Data for Scalable RDF Stream Processing,poster,Poster,49,Sejin Chun,paper49.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_song_17,17,"Zhenyu Song, Xiaowang Zhang and Zhiyong Feng",song,PRONA: A Plugin for Well-Designed Approximate Queries in Jena,poster,Poster,35,Zhenyu Song,paper17.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_fang_18,18,Hong Fang and Xiaowang Zhang,fang,pSPARQL: A Querying Language for Probabilistic RDF (Extended Abstract),poster,Poster,36,Hong Fang ,paper18.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_nguyen_7,7,Khai Nguyen and Ryutaro Ichise,nguyen,Ranking Feature for Classifier-based Instance Matching,poster,Poster,33,Khai Nguyen ,paper7.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_hartig_21,21,Olaf Hartig and Carlos Buil-Aranda,hartig,Reducing the Network Load of Triple Pattern Fragments by Supporting Bind Joins,poster,Poster,53,Olaf Hartig ,paper21.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_lenz_34,34,"Kai Lenz, Hiroshi Masuya and Norio Kobayashi",lenz,RIKEN MetaDatabase: a Database Publication Platform for RIKENs Life-science Researchers that Promotes Research Collaborations over Different Research Area,poster,Poster,24,Kai Lenz,paper34.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_de_paepe_55,55,"Dieter De Paepe, Ruben Verborgh and Erik Mannens",de paepe,Rule-Based Reasoning using State Space Search,poster,Poster,40,Dieter De Paepe,paper55.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_ternai_81,81,Katalin Ternai and Ildikó Szabó,ternai,Semantic Audit Application,poster,Poster,29,Katalin Ternai ,paper81.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_konstantpopoulos_33,33,"Stasinos Konstantopoulos, Angelos Charalambidis, Giannis Mouchakis, Antonis Troumpoukis, Jürgen Jakobitsch and Vangelis Karkaletsis",konstantpopoulos,Semantic Web Technologies and Big Data Infrastructures: SPARQL Federated Querying of Heterogeneous Big Data Stores,poster,Poster,27,Stasinos Konstantopoulos,paper33.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_debruyne_14,14,"Christophe Debruyne, Eamonn Clinton, Lorraine McNerney, Atul Nautiyal and Declan O'Sullivan",debruyne,Serving Ireland's Geospatial Information as Linked Data,poster,Poster,05,Christophe Debruyne,paper14.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_jouault_45,45,"Corentin Jouault, Kazuhisa Seta and Yuki Hayashi",jouault,SOLS: A Semantically Enriched Learning System Using LOD Based Automatic Question Generation,poster,Poster,11,Corentin Jouault,paper45.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_blinkiewicz_62,62,Jarosław Bąk and Michał Blinkiewicz,blinkiewicz,SQuaRE: A Visual Tool For Creating R2RML Mappings,poster,Poster,09,Jarosław Bąk ,paper62.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_wang_64,64,"Changlong Wang, Xiaowang Zhang and Zhiyong Feng",wang,Structure-guiding Modular Reasoning for Expressive Ontologies,poster,Poster,38,Changlong Wang,paper64.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_zhang_36,36,"Wei Emma Zhang, Ermyas Abebe, Quan Z. Sheng and Kerry Taylor",zhang,Towards Building Open Knowledge Base From Programming Question-Answering Communities,poster,Poster,13,Wei Emma Zhang,paper36.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_gravier_51,51,Christophe Gravier and Julien Subercaze,gravier,USE-RB : Benchmarking how Reasoners Work in Harmony with Modern Hardware,poster,Poster,51,Christophe Gravier ,paper51.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_wohlgenannt_37,37,Gerhard Wohlgenannt and Filip Minic,wohlgenannt,Using word2vec to Build a Simple Ontology Learning System,poster,Poster,15,Gerhard Wohlgenannt ,paper37.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_gassen_65,65,"Jonas Bulegon Gassen, Stefano Faralli, Simone Paolo Ponzetto and Jan Mendling",gassen,Who-Does-What: A Knowledge Base of People's Occupations and Job Activities,poster,Poster,20,Jonas Bulegon Gassen,paper65.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_watanabe_11,11,"Masao Watanabe, Kazunari Hashimoto, Seiya Inagi, Yohei Yamane, Seiji Suzuki and Hiroshi Umemoto",watanabe,Working Process Quantification in Factory Using Wearable Sensor Device and Ontology-based Stream Data Processing,poster,Poster,01,Masao Watanabe,paper11.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -poster_lee_103,103,"Jongmin Lee, Youngkyoung Ham and Tony Lee",lee,XB: A Large-scale Korean Knowledge Base for Question Answering Systems,poster,Poster,12,Jongmin Lee,paper103.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  -research_alshukali_8,8,"Duhai Alshukaili, Alvaro A. A. Fernandes and Norman Paton",alshukali,Structuring Linked Data Search Results Using Probabilistic Soft Logic,research,Search (I),2,Duhai Alshukaili,paper_M38_.pdf,502,2016-10-20T13:30:00,2016-10-20T14:50:00,"On-the-fly generation of integrated representations of Linked Data (LD)
  -  search results is challenging because it requires successfully automating a number
  -  of complex subtasks, such as structure inference and matching of
  -  both instances and concepts, each of which gives rise to uncertain
  -  outcomes. Such uncertainty is unavoidable given the semantically heterogeneous
  -  nature of web sources, including LD ones. This paper approaches the problem of 
  -  structuring LD search results as an evidence-based one. In particular, the paper shows 
  -  how one formalism (viz., probabilistic soft logic (PSL)) can be exploited to assimilate
  -  different sources of evidence in a principled way and to beneficial
  -  effect for users. The paper considers syntactic evidence derived from matching
  -  algorithms, semantic evidence derived from LD vocabularies, and user
  -  evidence, in the form of feedback. The main contributions are: sets 
  -  of PSL rules that model the uniform assimilation of diverse kinds of evidence, 
  -  an empirical evaluation of how the resulting PSL programs perform in terms 
  -  of their ability to infer structure in LD search results, and, finally, a concrete
  -  example of how populating such inferred structures for presentation
  -  to the end user is beneficial, besides enabling the collection of
  -  feedback whose assimilation further improves search result presentation."
  -research_angles_33,33,Renzo Angles and Claudio Gutierrez,angles,The multiset semantics of SPARQL patterns,research,Querying,1,Renzo Angles ,paper_M232_.pdf,502,2016-10-19T14:00:00,2016-10-19T15:20:00,"The paper determines the algebraic and logic structure produced by  the multiset semantics of the core patterns of SPARQL. We prove that the fragment formed by AND, UNION, OPTIONAL, FILTER, MINUS and SELECT corresponds precisely to both, the intuitive multiset relational algebra (projection, selection, natural join, arithmetic union and except), and multiset classical non-recursive Datalog with safe negation."
  -research_bereta_19,19,Konstantina Bereta and Manolis Koubarakis,bereta,Ontop of Geospatial Databases,research,Querying/SPARQL (II),4,Konstantina Bereta ,paper_M98_.pdf,502,2016-10-21T13:30:00,2016-10-21T14:50:00,"In this paper we propose an OBDA approach for accessing geospatial data stored in geospatial relational databases, using the OGC standard GeoSPARQL and R2RML or OBDA mappings. We introduce  extensions  to existing SPARQL-to-SQL approaches to support GeoSPARQL features. We describe the implementation of our approach in the system ontop-spatial, an extension of the OBDA system Ontop for creating  virtual geospatial RDF graphs on top of geospatial relational databases. Last, we present an experimental evaluation of our system using workload and queries from a  recent benchmark. In order to measure the performance of our system,  we compare it to the state-of-the-art geospatial RDF store, and confirm its efficiency."
  -research_brasileiro_11,11,"Freddy Brasileiro, Joao Paulo Almeida, Victorio Albani Carvalho and Giancarlo Guizzardi",brasileiro,Expressive Multi-Level Modeling for the Semantic Web,research,Knowledge Representation,4,Freddy Brasileiro,paper_M177_.pdf,502,2016-10-19T11:00:00,2016-10-19T12:20:00,"The assessment of risk in medicine is a crucial task, depending on scientific knowledge derived by rigorous clinical studies regarding the (quantified) factors affecting biological changes, as well as on particular knowledge about the current status of a particular patient. Existing non-semantic risk prediction tools are typically based on hardcoded scientific knowledge, and only cover a very limited range of patient states. This makes them rapidly out of date, and limited in application, particularly for patients with co-morbidities (multiple co-occurring conditions). Semantic Web and Quantified Self technologies make it possible to address this task in a much more principled way, to maximise knowledge and data reuse and minimise maintenance requirements while enabling new and sophisticated applications involving widely-available biometric sensors. 
  -
  -We present a framework for calculating clinical risk predictions for patients based on automatically-gathered biometric data. This framework relies on generic, reusable ontologies for representing clinical risk, and sensor readings, and reasoning to support the integration of data represented according to these ontologies. This integration makes novel use of Semantic Web technologies, and supports straightforward extension and maintenance by medical professionals. The framework is evaluated in terms of its predictions, extensibility and ease of use for domain experts."
  -research_carral_6,6,"David Carral, Cristina Feier and Pascal Hitzler",carral,A Practical Acyclicity Notion for Query Answering over Horn-SRIQ Ontologies,research,Reasoning,1,David Carral,paper_M202_.pdf,504+505,2016-10-21T15:30:00,2016-10-21T16:50:00,"Conjunctive query answering over expressive Horn Description Logic ontologies is a relevant and challenging problem which, in some cases, can be addressed by application of the chase algorithm.
  -In this paper, we define a novel acyclicity notion which provides sufficient condition for termination of the restricted chase over Horn-SRIQ ontologies.
  -We show that our notions generalize most of the existing acyclicity conditions (both theoretically and empirically) and its use results in a more efficient reasoning procedure.
  -Furthermore, we implement a materialization based reasoner for acyclic ontologies which vastly outperforms state-of-the-art reasoners.
  -"
  -research_chen_17,17,"Jiaqiang Chen, Niket Tandon, Charles Darwis Hariman and Gerard de Melo",chen,WebBrain: Joint Neural Learning of Large-Scale Commonsense Knowledge,research,Embeddings & Neural Approaches,1,Jiaqiang Chen,paper_M108_.pdf,502,2016-10-20T15:30:00,2016-10-20T16:50:00,"While massive volumes of text are now more easily available for knowledge harvesting, many important facts about our everyday world are not expressed in a particularly explicit way. To address this, we present WebBrain, a new approach for harvesting commonsense knowledge that relies on joint learning from Web-scale data to fill gaps in the knowledge acquisition. We train a neural network model that not only learns word2vec-style vector representations of words but also commonsense knowledge about them. This joint model allows general semantic information to aid in generalizing beyond the extracted commonsense relationships. Experiments show that we can obtain word embeddings that reflect word meanings, yet also allow us to capture conceptual relationships and commonsense knowledge about them."
  -research_cheng_13,13,"Gong Cheng, Daxin Liu and Yuzhong Qu",cheng,Efficient Algorithms for Association Finding and Frequent Association Pattern Mining,research,Data Mining,1,Gong Cheng,paper_M25_.pdf,502,2016-10-21T10:30:00,2016-10-21T11:50:00,"Finding associations between entities is a common information need in many areas. It has been facilitated by the increasing amount of graph-structured data on the Web describing relations between entities. In this paper, we define an association connecting multiple entities in a graph as a minimal connected subgraph containing all of them. We propose an efficient graph search algorithm for finding associations, which prunes the search space by exploiting distances between entities computed based on a distance oracle. Having found a possibly large group of associations, we propose to mine frequent association patterns as a conceptual abstract summarizing notable subgroups to be explored, and present an efficient mining algorithm based on canonical codes and partitions. Extensive experiments on large, real RDF datasets demonstrate the efficiency of the proposed algorithms."
  -research_christen_37,37,"Victor Christen, Anika Groß and Erhard Rahm",christen,A Reuse-based Annotation Approach for Medical Documents,research,Medical Applications,2,Victor Christen,paper_M163_.pdf,501,2016-10-21T13:30:00,2016-10-21T14:50:00,"Annotations are useful to semantically enrich documents and other datasets with concepts of standardized vocabularies and ontologies. In the medical domain, many documents are not annotated at all and manual annotation is a difficult and time-consuming process. Therefore, automatic annotation methods become necessary to support human annotators with recommendations. We propose a reuse-based annotation approach that clusters items in medical documents according to verified ontology-based annotations. We identify a set of representative features for annotation clusters and propose a context-based selection strategy that considers the semantic relatedness and frequent co-occurrences of annotated concepts. We evaluate our methods and the annotation tool MetaMap based on reference mappings between medical forms and the Unified Medical Language System."
  -research_cochez_26,26,"Michael Cochez, Stefan Decker and Eric Prud'Hommeaux",cochez,Knowledge Representation on the Web revisited: the Case for Prototypes,research,Knowledge Representation,1,Michael Cochez,paper_M224_.pdf,502,2016-10-19T11:00:00,2016-10-19T12:20:00,"The goal of this work is to learn a measure supporting the detection of strong relationships between Linked Data entities. Such relationships can be represented as paths of entities and properties, and can be obtained through a blind graph search process traversing Linked Data. The challenge here is therefore the design of a cost-function that is able to detect the strongest relationship between two given entities, by objectively assessing the value of a given path. To achieve this, we use a Genetic Programming approach in a supervised learning method to generate path evaluation functions that compare well with human evaluations. We show how such a cost-function can be generated only using basic topological features of the nodes of the paths as they are being traversed (i.e. without knowledge of the whole graph), and how it can be improved through introducing a very small amount of knowledge about the vocabularies of the properties that connect nodes in the graph."
  -research_degiacomo_12,12,"Giuseppe De Giacomo, Xavier Oriol, Riccardo Rosati and Domenico Fabio Savo",degiacomo,Updating DL-Lite Ontologies through First-Order Queries,research,Reasoning,2,Giuseppe De Giacomo,paper_M68_.pdf,504+505,2016-10-21T15:30:00,2016-10-21T16:50:00,"In this paper we study instance-level update in DL-LiteA, the description logic underlying the OWL 2 QL standard. In particular we focus on formula based approaches to ABox insertion and deletion. We show that DL-LiteA, which is well known for enjoying first-order rewritability  of query answering, enjoys a first-order rewritability property also for updates. That is, every update can be reformulated into a set of insertion and deletion instructions computable through a non-recursive DATALOG program. Such a program is readily translatable into a first-order query  over the ABox considered as a database, and hence into SQL. Exploiting this result we implement an update component for DL-LiteA-based systems and perform some experiments  showing that the approach works in practice."
  -research_derooij_36,36,"Steven de Rooij, Wouter Beek, Peter Bloem, Frank van Harmelen and Stefan Schlobach",derooij,Are Names Meaningful? Quantifying Social Meaning on the Semantic Web,research,Linked Data Measurement,1,Steven de Rooij,paper_M210_.pdf,504+505,2016-10-20T13:30:00,2016-10-20T14:50:00,"According to Semantic Web standards, IRIs are individual
  -constants or predicate letters whose names are chosen arbitrarily
  -and carry no formal meaning.  At the same time it is a well-known
  -aspect of Semantic Web pragmatics that IRIs are often constructed
  -mnemonically, in order to be meaningful to a human interpreter.
  -The latter has traditionally been termed 'Social Meaning', a
  -concept that has been discussed but not yet quantitatively
  -studied by the Semantic Web community.
  -
  -In this paper we use statistical model learning as a method to
  -quantify the meaning that is (at least) encoded in Semantic Web
  -names, We implement the approach and evaluate it over hundreds of
  -thousands of data sets in order to illustrate its efficacy.  Our
  -experiments confirm that many Semantic Web names are indeed
  -meaningful and, more interestingly, we provide a quantitative
  -lower bound on how much meaning is (at least) encoded in names on
  -a per-dataset basis.
  -
  -To our knowledge, this is the first paper about the interaction
  -between social and formal meaning, as well as the first paper
  -that uses statistical model learning as a method to quantify
  -meaning in the Semantic Web context.
  -"
  -research_dragisic_39,39,"Zlatan Dragisic, Valentina Ivanova, Patrick Lambrix, Daniel Faria, Ernesto Jiménez-Ruiz and Catia Pesquita",dragisic,User validation in ontology alignment,research,Ontology Matching,3,Zlatan Dragisic,paper_M146_.pdf,504+505,2016-10-20T10:30:00,2016-10-20T11:50:00,"User validation is one of the challenges facing the ontology alignment community, as there are limits to the quality of automated alignment algorithms.
  -In this paper we present a broad study on user validation of ontology alignments that encompasses three distinct but interrelated aspects: the profile of the user, the services of the alignment system, and its user interface. We discuss key issues pertaining to the alignment validation process under each of these aspects, and provide an overview of how current systems address them. Finally, we use experiments from the Interactive Matching track of the Ontology Alignment Evaluation Initiative (OAEI) 2015 to assess the impact of errors in alignment validation, and how systems cope with them as function of their services."
  -research_eldesouky_4,4,"Bahaa Eldesouky, Menna Bakry, Heiko Maus and Andreas Dengel",eldesouky,"Seed, an End-user Text Composition Tool for the Semantic Web",research,Interaction,1,Bahaa Eldesouky,paper_M242_.pdf,504+505,2016-10-19T11:00:00,2016-10-19T12:20:00,"Despite developments of Semantic Web-enabling technologies,
  -the gap between non-expert end-users and the Semantic Web still
  -exists. In the field of semantic content authoring, tools for interacting
  -with semantic content remain directed at highly trained individuals. This
  -adds to the challenges of bringing user-generated content into the Semantic
  -Web.
  -In this paper, we present Seed, short for Semantic Editor, an extensible
  -knowledge-supported natural language text composition tool, which
  -targets non-experienced end-users enabling automatic as well as semiautomatic
  -creation of standards based semantically annotated textual
  -content. We point out the structure of Seed, compare it with related
  -work and explain how it utilizes Linked Open Data and state of the art
  -Natural Language Processing to realize user-friendly generation of textual
  -content for the Semantic Web. We also present experimental evaluation
  -results involving a diverse group of more than 120 participants,
  -which showed that Seed helped end-users easily create and interact with
  -semantic content with nearly no prerequisite knowledge."
  -research_gadelrab_29,29,"Mohamed H. Gad-Elrab, Daria Stepanova, Jacopo Urbani and Gerhard Weikum",gadelrab,Exception-enriched Rule Learning from Knowledge Graphs,research,Data Mining,4,Mohamed H. Gad-Elrab,paper_M139_.pdf,502,2016-10-21T10:30:00,2016-10-21T11:50:00,"Finding relevant concepts from a corpus of ontologies is useful in many scenarios, including document classification, web page annotation, and automatic ontology population. Millions of concepts are contained in a large number of ontologies across diverse domains. SPARQL-based query demands knowledge of the structure of ontologies and the query language, whereas more user-friendly, simple keyword-based approaches suffer from false positives as concept descriptions in ontologies may be ambiguous and overlapping. In this paper, we propose a keyword-based concept search framework that (1) exploits the structure and semantics in ontologies, by constructing contexts for each concept; (2) generates the interpretations of a query; and (3) balances relevance and diversity of search results. A comprehensive evaluation against both the domain-specific BioPortal and the general-purpose Falcons on widely-used performance metrics demonstrates that our system outperforms both."
  -research_gao_35,35,"Shen Gao, Daniele Dell'Aglio, Soheila Dehghanzadeh, Abraham Bernstein, Emanuele Della Valle and Alessandra Mileo",gao,Planning Ahead: Stream-Driven Linked-Data Access under Update-Budget Constraints,research,Streams,1,Shen Gao,paper_M119_.pdf,501,2016-10-20T13:30:00,2016-10-20T14:50:00,"Data stream applications are becoming increasingly popular on the web. In these applications, one query pattern is especially prominent: a join between a continuous data stream and some background data (BGD). Oftentimes, the target BGD is large, maintained externally, changing slowly, and costly to query (both in terms of time and money). Hence, practical applications usually maintain a local (cached) view of the relevant BGD. Given that these caches are not updated as part of the transaction modifying the original BGD, they should be maintained under realistic budget constraints (in terms of latency, computation time, and possibly financial cost) to avoid stale data leading to wrong answers. 
  -
  -This paper proposes to model the join between streams and the BGD as a bipartite graph. By exploiting the graph structure, we keep the quality of results good enough without refreshing the entire cache for each evaluation. We also introduce two extensions to this method: first, we consider both the sliding window (specifying the currently relevant section of the data stream) and the change rate of the BGD to focus on updates that have the longest effect. Second, by considering the future impact of a query to the BGD we propose to sometimes delay updates to provide more fresher answers in future.
  -
  -Using an implemented system we empirically show that we can improve result freshness by 93% over baseline algorithms such as Random Selection or Least Recently Updated."
  -research_gavankar_5,5,"Chetana Gavankar, Yuan-Fang Li and Ganesh Ramakrishnan",gavankar,Explicit Query Interpretation and Diversification for Context-driven Concept Search across Ontologies,research,Search (I),1,Chetana Gavankar,paper_M110_.pdf,502,2016-10-20T13:30:00,2016-10-20T14:50:00,"We build on our earlier finding that more than 95% of the triples in actual RDF triple graphs have a remarkably tabular structure, whose schema does not necessarily follow from explicit metadata such as ontologies, but which an RDF store can automatically derive by looking at the data using so-called ``emergent schema'' detection techniques. In this paper we investigate how computers and in particular RDF stores can take advantage from this emergent schema to more compactly store RDF data and more efficiently optimize and execute SPARQL queries. To this end, we contribute techniques for efficient emergent schema aware RDF storage and new query operator algorithms for emergent schema aware scans and joins. In all, these techniques allow RDF schema processors fully catch up with relational database techniques in terms of rich physical database design options and efficiency, without requiring a rigid upfront schema structure definition."
  -research_guclu_16,16,"Isa Guclu, Yuan-Fang Li, Jeff Z. Pan and Martin J. Kollingbaum",guclu,Predicting Energy Consumption of Ontology Reasoning over Mobile Devices,research,Smart Planet,1,Isa Guclu,paper_M304_.pdf,504+505,2016-10-19T14:00:00,2016-10-19T15:20:00,"The unprecedented growth in mobile devices, combined with advances in Semantic Web Technologies, has given birth to opportunities for more intelligent systems on-the-go. Limited resources of mobile devices, especially energy, demand approaches to make mobile reasoning more applicable. While Mobile-Cloud integration is a promising method for harnessing the power of semantic technologies in the mobile infrastructure, it is an open question on deciding when to reason with ontologies on mobile devices. In this paper, we introduce an energy consumption prediction mechanism for ontology reasoning on mobile devices, which allows analysis of feasibility of ontology reasoning on mobile devices in terms of energy consumption. The prediction models contributes to mobile-cloud integration and helps improve further development of ontology and semantic solutions in general."
  -research_hartig_31,31,Olaf Hartig and M. Tamer Özsu,hartig,Walking without a Map: Ranking-Based Traversal for Querying Linked Data,research,Search (II),4,Olaf Hartig ,paper_M164_.pdf,504+505,2016-10-20T15:30:00,2016-10-20T16:50:00,"The emergence of Linked Data on the WWW has spawned research interest in an online execution of declarative queries over this data. A particularly interesting approach is traversal-based query execution which fetches data by traversing data links and, thus, is able to make use of up-to-date data from initially unknown data sources. While the downside of this approach is the delay before the query engine completes a query execution, user perceived response time may be improved significantly by returning as many elements of the result set as soon as possible. To this end, the query engine requires a traversal strategy that enables the engine to fetch result-relevant data as early as possible. The challenge for such a strategy is that the query engine does not know a priori what data sources will be discovered during the query execution and which of them contain result-relevant data. In this paper, we investigate 14 different approaches to rank traversal steps and achieve a variety of traversal strategies. We experimentally study their impact on response times and compare them to a baseline that resembles a breadth-first traversal. While our experiments show that some of the approaches can achieve noteworthy improvements over the baseline in a significant number of cases, we also observe that for every approach, there is a non-negligible chance to achieve response times that are worse than the baseline."
  -research_hoffner_18,18,"Konrad Höffner, Jens Lehmann and Ricardo Usbeck",hoffner,CubeQA—Question Answering on RDF Data Cubes,research,Search (II),1,Konrad Höffner,paper_M10_.pdf,504+505,2016-10-20T15:30:00,2016-10-20T16:50:00,"Statistical data in the form of RDF Data Cubes is becoming increasingly valuable as it influences decisions in areas such as health care, policy and finance. While a growing amount is becoming freely available through the open data movement, this data is opaque to laypersons. Semantic Question Answering (SQA) technologies provide access via free-form natural language queries but general SQA systems cannot process RDF Data Cubes. On the intersection between RDF Data Cubes and SQA, we create a new subfield of SQA, called RDCQA. We create an RDQCA benchmark as task 3 of the QALD-6 evaluation challenge, to stimulate further research and enable quantitative comparison between RDCQA systems. We design and evaluate the CubeQA algorithm, which
  -is the first RDCQA system and achieves a global F 1 score of 0.43 on the QALD6T3-test dataset, showing that RDCQA is feasible."
  -research_ibragimov_7,7,"Dilshod Ibragimov, Katja Hose, Torben Bach Pedersen and Esteban Zimanyi",ibragimov,Optimizing Aggregate SPARQL Queries using Materialized RDF Views,research,Querying,3,Dilshod Ibragimov,paper_M127_.pdf,502,2016-10-19T14:00:00,2016-10-19T15:20:00,"During the past couple of years, more and more data has been published as native RDF datasets. In this setup, both the size of the datasets and the need to process aggregate queries represent challenges for standard SPARQL query processing techniques. To overcome these limitations, materialized views can be created and used as a source of precomputed partial results during query processing. However, materialized view techniques, as proposed in relational databases, do not support RDF specifics, such as incompleteness and the need to support implicit (derived) information. Therefore, to overcome these challenges, this paper proposes MARVEL – the approach consisting of a view selection algorithm based on an RDF-specific cost model, a view definition syntax. and an algorithm for rewriting SPARQL queries using materialized RDF views. The experimental evaluation shows that the approach can improve query response time by more than an order of magnitude and is able to efficiently handle RDF specifics."
  -research_inants_3,3,"Armen Inants, Manuel Atencia and Jérôme Euzenat",inants,Algebraic calculi for weighted ontology alignments,research,Ontology Matching,1,Armen Inants,paper_M149_.pdf,504+505,2016-10-20T10:30:00,2016-10-20T11:50:00,"Alignments between ontologies usually come with numerical attributes expressing the confidence of each correspondence. Semantics supporting such confidences must generalise the semantics of alignments without confidence. There exists a semantics which satisfies this but introduces a discontinuity between weighted and non-weighted interpretations. Moreover, it does not provide a calculus for reasoning with weighted ontology alignments. This paper introduces a calculus for such alignments. It is given by an infinite relation-type algebra, the elements of which are weighted taxonomic relations. In addition, it approximates the non-weighted case in a continuous manner."
  -research_krotzsch_24,24,Markus Krötzsch and Veronika Thost,krotzsch,Ontologies for Knowledge Graphs: Breaking the Rules,research,Knowledge Representation,2,Markus Krötzsch ,paper_M303_.pdf,502,2016-10-19T11:00:00,2016-10-19T12:20:00,"Large-scale knowledge graphs (KGs) abound in industry and academia. 
  +research_303,303,Markus Krötzsch and Veronika Thost,Krötzsch,Ontologies for Knowledge Graphs: Breaking the Rules,research,Knowledge Representation,2,Markus Krötzsch,research_303.pdf,502,2016-10-19T11:20:00,2016-10-19T11:40:00,"Large-scale knowledge graphs (KGs) abound in industry and academia. 
   They provide a unified format for integrating information sources, 
   aided by standards such as, e.g., the W3C RDB to RDF Mapping Language. 
   Meaningful semantic integration, however, is much harder than 
  
positive.code: number of total matching triples. By combining several tpfs, sparql queries are
  evaluated on the client-side, using the metadata for optimization. Hence, we can
  measure the query execution"
  doctoralconsortium_terziev_7,7,Yordan Terziev,terziev,Feature Generation using Ontologies during Induction of Decision Trees on Linked Data,doctoralconsortium,Session 2,6,Yordan Terziev,DC_Terziev.pdf,,2016-10-18T09:00:00,2016-10-18T17:30:00,"Linked data has the potential of interconnecting data from different domains, bringing new potentials to machine agents to provide better services for web users. The ever increasing amount of linked data in government open data, social linked data, linked medical and patients’ data provides new opportuni-ties for data mining and machine learning. Both are however strongly de-pendent on the selection of high quality data features to achieve good results. In this work we present an approach that uses ontological knowledge to gen-erate features that are suitable for building a decision tree classifier address-ing the specific data set and classification problem. The approach that we present has two main characteristics - it generates new features on demand as required by the induction algorithm and uses ontological knowledge about linked data to restrict the set of possible options. These two characteristics enable the induction algorithm to look for features that might be connected through many entities in the linked data enabling the generation of cross-domain explanation models."
  doctoralconsortium_ahn_9,9,Jinhyun Ahn,ahn,Optimization Techniques for 2-hop Labeling of Dynamic Directed Acyclic Graphs,doctoralconsortium,Session 2,7,Jinhyun Ahn,DC_Ahn.pdf,,2016-10-18T09:00:00,2016-10-18T17:30:00,"Directed Acyclic Graph(DAG) data is increasingly available on the Web, including Linked Open Data(LOD). Mining reachability relationships between entities is an important task for extracting knowledge from LOD. Diverse labeling schemes have been proposed to efficiently determine the reachability. We focus on a state-of-the-art 2-hop labeling scheme that is based on a permutation of vertices to achieve a linear index size and reduce on-line searches that are required when the reachability cannot be answered by 2-hop labels only. We observed that the approach can be improved in three different ways; 1) space-efficiency - guarantee the minimized index size without randomness 2) update-efficiency - update labels efficiently when graphs changes 3) parallelization - labeling should be cluster-based, and solved in a distributed fashion. In these regards, this PhD thesis proposes optimization techniques that address these issues. In this paper in particular, a way of reducing the 2-hop label size is proposed with preliminary results on real-world DAG datasets. In addition, we will discuss the feasibilities of the other issues based on our on-going works."
  doctoralconsortium_ren_11,11,Xiangnan Ren,ren,"Towards a distributed, scalable and real-time RDF Stream Processing engine",doctoralconsortium,Session 2,8,Xiangnan Ren,DC_Ren.pdf,,2016-10-18T09:00:00,2016-10-18T17:30:00,"Due to the growing need to timely process and derive valuable information and knowledge from data produced in the Semantic Web, RDF stream processing (RSP) has emerged as an important research domain. Of course, modern RSP have to address the volume and velocity characteristics encountered in the Big Data era. This comes at the price of designing high throughput, low latency, fault tolerant, highly available and scalable engines. The cost of implementing such systems from scratch is very high and usually one prefers to program components on top of a framework that possesses these properties, e.g., Apache Hadoop or Apache Spark. The research conducting in this PhD adopts this approach and aims to create a production-ready RSP engine which will be based on domain standards, e.g., Apache Kafka and Spark Streaming. In a nutshell, the engine aims to i) address basic event modeling - to guarantee the completeness of input data in window operators, ii) process real-time RDF stream in a distributed manner - efficient RDF stream handling is required; iii) support and extend common continuous SPARQL syntax - easy-to-use, adapt to the industrial needs and iv) support reasoning services at both the data preparation and query processing levels."
  doctoralconsortium_georgala_2,2,Kleanthi Georgala,georgala,Scalable Link Discovery for Modern Data-Driven Applications,doctoralconsortium,Session 2,9,Kleanthi Georgala,DC_Georgaia.pdf,,2016-10-18T09:00:00,2016-10-18T17:30:00,"Modern data-driven applications often have to integrate and process large volumes of high-velocity data. To this end, they require fast and accurate Link Discovery solutions. Most Link Discovery frameworks rely on complex link specifications to determine candidates for links. Hence, the main focus of this work lies in the conception, development, implementation and evaluation of time-efficient and scalable Link Discovery approaches based on the link specification paradigm. We address the aforementioned challenges by presenting approaches for (1) time-constrained linking and (2) for the efficient computation and (3) scalable execution of link specifications with applications to periodically updated knowledge bases. The overall result of this thesis will be an open-source framework for link discovery on large volumes of RDF data streams."
  doctoralconsortium_masuda_12,12,Takeshi Masuda,masuda,Ontology Refinement and Evaluation System based on Similarity of Is-a Hierarchies,doctoralconsortium,Session 3,10,Takeshi Masuda,DC_Masuda,,2016-10-18T09:00:00,2016-10-18T17:30:00,"Ontologies are constructed in various fields such as medical information, mechanical design, and etc. It is important to build high quality ontologies so that these ontologies are used as knowledge bases and knowledge models for application systems. However it is hard to build good quality ontologies because of the necessity of both knowledge of ontology and expertise in their target domain. For this background, ontology construction and refinement costs a lot of time and ef-fort. In order to reduce such costs, we develop an ontology refinement support system. This system have two main function. First, the system can detect points that should be refined and propose how to refine it. Second, the system can evaluate ontologies quantitatively. This system indicate how ontologies are consistent in a classificatory criterion. To develop the refinement support system, we focus on a guideline for building well-organized ontologies that “Each subclass of a super class is distinguished by the values of exactly one attribute of the super class”. When an ontology is built following this guideline, there is similarity among Is-a hierarchies. We use these similar Is-a hierarchies and develop an ontology refinement system."
  doctoralconsortium_ivanova_4,4,Valentina Ivanova,ivanova,Applications of Large Displays: Advancing User Support in Large Scale Ontology Alignment,doctoralconsortium,Session 3,11,Valentina Ivanova,DC_Ivanova.pdf,,2016-10-18T09:00:00,2016-10-18T17:30:00,"Producing alignments of highest quality requires ‘humans in the loop’, however, user involvement is currently one of the challenges for the ontology alignment community. Ontology alignment is a cognitively intensive task and could be efficiently supported by user interfaces encompassing well-designed visualizations and interaction techniques. This work investigates the application of large, high-resolution displays to improve users’ cognitive support and identifies several promising directions for their application—improving ontologies’ and alignments’ navigation, supporting users’ thinking process and collaboration."
  doctoralconsortium_neumaier_13,13,Sebastian Neumaier,neumaier,Improving Open Data Usability through Semantics,doctoralconsortium,Session 3,12,Sebastian Neumaier,DC_Neumaier.pdf,,2016-10-18T09:00:00,2016-10-18T17:30:00,"With the success of Open Data a huge amount of tabular data become available that could potentially be mapped and linked into the Web of (Linked) Data. The use of semantic web technologies would then allow to explore related content and enhanced search functionalities across data portals. However, existing linkage and labeling approaches mainly rely on mappings of textual information to classes or properties in knowledge bases. In this work we outline methods to recover the semantics of tabular Open Data and to identify related content which allows a mapping and automated integration/categorization of Open Data resources and improves the overall usability and quality of Open Data."
  doctoralconsortium_van_herwegen_8,8,Joachim Van Herwegen,van herwegen,Querying Distributed Heterogeneous Linked Data Interfaces through Reasoning,doctoralconsortium,Session 3,13,Joachim Van Herwegen,DC_VanHerwegen.pdf,,2016-10-18T09:00:00,2016-10-18T17:30:00,"Linked Data can be distributed through multiple interfaces on the Web,
  each of them with their own expressivity.
  However, there is no generic client available that can handle querying over multiple interfaces.
  This increases the complexity of combining datasets and designing new interfaces.
  
negative.code: ID,NR,Authors,Lastname,Title,Track,Session,PIndex,Presenter,file,Room,Start,End,Abstract
  demo_48,48,Jędrzej Potoniec and Agnieszka Ławrynowicz,Potoniec,A Protege Plugin with Swift Linked Data Miner,demo,Poster and Demo session,1,Jędrzej Potoniec,demo_48.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"We present a Protege plugin implementing Swift Linked Data Miner, an anytime algorithm for extending an ontology with new subsumptions. The algorithm mines an RDF graph accessible via a SPARQL endpoint and proposes new SubClassOf axioms to the user."
  demo_114,114,"Pasquale Lisena, Manel Achichi, Eva Fernandez, Konstantin Todorov and Raphaël Troncy",Lisena,Exploring Linked Classical Music Catalogs with OVERTURE,demo,Poster and Demo session,2,Pasquale Lisena,demo_114.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this paper, we introduce OVERTURE - a web application allowing to explore the interlinked catalogs of major music libraries including the French National Library, Radio France and the Philharmonie de Paris. We have first developed the DOREMUS ontology which is an extension of the well-known FRBRoo model for describing works and expressions as well as the creation processus. We have implemented a so-called marc2rdf tool allowing for the conversion and linking of bibliographical entries about music works, interpretations and expressions from their original MARC-format to RDF following this DOREMUS ontology. We present an exploratory search engine prototype that enables to browse through the reconciled collection of bibliographical records of classical music and to highlight the various interpretations of a work, its derivative, its performance casting as well as other rich metadata."
  poster_23,23,John P. Mccrae and Philipp Cimiano,Mccrae,"LIXR: Quick, succinct conversion of XML to RDF",poster,Poster and Demo session,25,John P. Mccrae,poster_23.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"This paper presents LIXR, a system for converting between RDF and XML. LIXR is based on domain-specific language embedded into the Scala programming language. It supports the definition of transformations of datasets from RDF to XML in a declarative fashion, while still maintaining the flexibility of a full programming language environment. We directly compare this system to other systems programmed in Java and XSLT and show that the LIXR implementations are significantly shorter in terms of lines of code, in addition to being bidirectional and conceptually simple to understand.
  "
  demo_116,116,"Konstantina Bereta, Guohui Xiao, Manolis Koubarakis, Martina Hodrius and Conrad Bielski",Bereta,Ontop-spatial for Geospatial Data Integration using GeoSPARQL-to-SQL Translation,demo,Poster and Demo session,4,Konstantina Bereta,demo_116.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"We present Ontop-spatial, a geospatial extension of the well-known OBDA system Ontop, that leverages the technologies of geospatial databases and enables GeoSPARQL-to-SQL translation. We showcase the functionalities of the system in real-world use cases which require data integration of different geospatial sources."
  demo_42,42,"Nandana Mihindukulasooriya, Esteban Gonzalez, Fernando Serena, Carlos Badenes and Oscar Corcho",Mihindukulasooriya,FarolApp: Live Linked Data on Light Pollution,demo,Poster and Demo session,5,Nandana Mihindukulasooriya,demo_42.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"FarolApp is a mobile web application that aims to increase the awareness of light pollution by generating illustrative maps for cities and by encouraging citizens and public administrations to provide street light information in an ubiquitous and interactive way using online street views. In addition to the maps, FarolApp builds on existing sources to generate and provide up-to-date data by crowdsourced user annotations. Generated data is available as dereferenceable Linked Data resources in several RDF formats and via a queryable SPARQL endpoint. The demo presented in this paper illustrates how FarolApp maintains continuously evolving Linked Data that reflect the current status of city street light infrastructures and use that data to generate light pollution maps."
  demo_47,47,"Alo Allik, Mariano Mora-Mcginity, Gyorgy Fazekas and Mark Sandler",Allik,MusicWeb: music discovery with open linked semantic metadata,demo,Poster and Demo session,6,Alo Allik,demo_47.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"This demo presents MusicWeb, a novel platform for linking music artists within a web-based application for discovering associations between them. MusicWeb provides a browsing experience using connections that are either extra-musical or tangential to music, such as the artists' political affiliation or social influence, or intra-musical, such as the artists' main instrument or most favoured musical key. The platform integrates open linked semantic metadata from various Semantic Web, music recommendation and social media data sources. The connections are further supplemented by thematic analysis of journal articles, blog posts and content-based similarity measures focussing on high level musical categories."
  demo_113,113,"Jacopo Urbani, Ceriel Jacobs and Markus Krötzsch",Urbani,VLog: A Column-Oriented Datalog System for Large Knowledge Graphs,demo,Poster and Demo session,7,Jacopo Urbani,demo_113.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"We present VLog, a new system for answering arbitrary Datalog queries on top of a wide range of databases, including both relational and RDF databases. VLog is designed to perform efficiently intensive rule-based computation on large Knowledge Graphs (KGs). It adapts column-store technologies to attain high efficiency in terms of memory usage and speed, enabling us to process Datalog queries with thousands of rules over databases with hundreds of millions of tuples---in a live demonstration on a laptop. Our demonstration provides in-depth insights into the workings of VLog, and presents important new features such as support for arbitrary relational DBMS."
  poster_81,81,Katalin Ternai and Ildikó Szabó,Ternai,Semantic Audit Application,poster,Poster and Demo session,8,Katalin Ternai,poster_81.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Compliance checking of business processes executed by auditors requires to analyze documents e.g. log files, business process models depending on requirements derived from reference guidelines. This paper presents a forward compliance checking application for facilitating conformant behavior by de-tecting organizational operations and their deviations based on these docu-ments in a semantic way. This application has been tested on the Internaliza-tion process in the respect of Erasmus mobility."
  poster_82,82,"Davide Lanti, Guohui Xiao and Diego Calvanese",Lanti,An Evaluation of VIG with the BSBM Benchmark,poster,Poster and Demo session,9,Davide Lanti,poster_82.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this paper we present an experimental evaluation of VIG, a data scaler for OBDA benchmarks. Data scaling is a relatively recent approach, proposed in the database community, that allows for quickly scaling an input data instance to s times its size, while preserving certain application-specific characteristics. The advantages of scaling are that the generator is general, in the sense that it can be re-used on different database schemas, and that users are not required to manually input the data characteristics. VIG lifts the scaling approach from the database level to the OBDA level, where the domain information of ontologies and mappings has to be taken into account as well.
   To evaluate the quality of VIG, in this paper we use it to generate data for the Berlin SPARQL Benchmark (BSBM), and compare it with the official BSBM data generator."
  poster_85,85,"Seungjun Yoon, Sejin Chun, Xiongnan Jin and Kyong-Ho Lee",Yoon,A Unified Interface for Optimizing Continuous Query in Heterogeneous RDF Stream Processing Systems,poster,Poster and Demo session,10,Seungjun Yoon,poster_85.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"The W3C RDF Stream Processing (RSP) community has proposed both a common model and a language for querying RDF streams. However, the current implementations of RSP systems are significantly different from each other in terms of performance. In this paper, we propose a unified interface for optimizing a continuous query in heterogeneous RSP systems. To enhance the performance of RSP, the unified interface decomposes query, reassembles partial queries and assigns them to appropriate RSP systems. Experimental results show that the proposed approach performances better in terms of memory consumption and latency."
  poster_86,86,"Silvio Peroni, David Shotton and Fabio Vitali",Peroni,Jailbreaking your reference lists: the OpenCitations strike again,poster,Poster and Demo session,11,Silvio Peroni,poster_86.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this poster paper we provide an overview of the OpenCitations project and of its main outcome, the OpenCitations Corpus, which is an open repository of scholarly citation data made available under a Creative Commons public domain dedication, which provides in RDF accurate citation information harvested from the scholarly literature."
  poster_8,8,Jing Mei,Mei,Building Evidence Graph for Clinical Decision Support,poster,Poster and Demo session,27,Jing Mei,poster_8.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Evidence-based medicine intends to optimize clinical decision making by using evidence. Semantic query answering could help to find the most relevant evidence. However, at point of care, it still lacks time for human reading of the evidence. In this poster, we propose to build an evidence graph for clinical decision support, in which an evidence ontology is defined with extension of SWRL rules. On top of this graph, we do evidence query and evidence fusion to generate the ranking list of decision options. Our prototype implementation of the evidence graph demonstrates its assistance to decision making, by combining a variety of knowledge-driven and data-driven decision services."
  resource_23,23,"Wei Hu, Haoxuan Li, Zequn Sun, Xinqi Qian, Lingkun Xue, Ermei Cao and Yuzhong Qu",Hu,Clinga: Bringing Chinese Physical and Human Geography in Linked Open Data,resource,Linked Data,4,Wei Hu,resource_23.pdf,504+505,2016-10-20T11:30:00,2016-10-20T11:50:00,"While the geographical domain has long been involved as an important part of the Linked Data, the small amount of Chinese linked geographical data hinders the integration and sharing of both Chinese and cross-lingual knowledge. In this paper, we contribute to the development of a new Chinese linked geographical dataset named Clinga, by obtaining data from the largest Chinese wiki encyclopedia. We manually design a new geography ontology to categorize a wide range of physical and human geographical entities, and carry out an automatic discovery of links to existing knowledge bases. The resulted Clinga dataset contains over half million Chinese geographical entities and is open access."
  research_108,108,Gerard de Melo,Melo,WebBrain: Joint Neural Learning of Large-Scale Commonsense Knowledge,research,Embeddings & Neural Approaches,1,Gerard de Melo,research_108.pdf,502,2016-10-20T15:30:00,2016-10-20T15:50:00,"While massive volumes of text are now more easily available for knowledge harvesting, many important facts about our everyday world are not expressed in a particularly explicit way. To address this, we present WebBrain, a new approach for harvesting commonsense knowledge that relies on joint learning from Web-scale data to fill gaps in the knowledge acquisition. We train a neural network model that not only learns word2vec-style vector representations of words but also commonsense knowledge about them. This joint model allows general semantic information to aid in generalizing beyond the extracted commonsense relationships. Experiments show that we can obtain word embeddings that reflect word meanings, yet also allow us to capture conceptual relationships and commonsense knowledge about them."
  resource_27,27,"Roberto Garcia, Rosa Gil, Juan Manuel Gimeno, Eirik Bakke and David Karger",Garcia,Benchmarking End-User Structured Data Search and Exploration,resource,Interaction,2,Roberto Garcia,resource_27.pdf,504+505,2016-10-19T11:20:00,2016-10-19T11:40:00,"The Semantic Web Community has invested significant research effort in developing systems for Semantic Web search and exploration. But while it has been easy to assess the systems' computational efficiency, it has been much harder to assess how well different semantic systems help their users find and browse information. In this article, we propose and demonstrate the use of a benchmark for evaluating them, similar to the TREC benchmark for evaluating traditional search engines. Our benchmark includes a set of typical user tasks and a well-defined procedure for assigning a measure of performance on those tasks to a semantic system. We demonstrate its application to one such system, Rhizomer. We intend for this work to initiate a community conversation that will lead to a general accepted framework for comparing systems and measuring, and thus encouraging, progress towards better semantic search and exploration tools."
  resource_28,28,"Silvio Peroni, Giorgia Lodi, Luigi Asprino, Aldo Gangemi and Valentina Presutti",Peroni,FOOD: FOod in Open Data,resource,Linked Data,2,Silvio Peroni,resource_28.pdf,504+505,2016-10-20T10:50:00,2016-10-20T11:10:00,"This paper describes the outcome of an e-government project named FOOD, FOod in Open Data, which was carried out in the context of a collaboration between the Institute of Cognitive Sciences and Technologies of the Italian National Research Council, the Italian Ministry of Agriculture (MIPAAF) and the Italian Digital Agency (AgID). In particular, we implemented several ontologies for describing protected names of products (wine, pasta, fish, oil, etc.). In addition, we present the process carried out for producing and publishing a LOD dataset containing data extracted from existing Italian policy documents on such products and compliant with the aforementioned ontologies."
  research_107,107,"Mohsen Taheriyan, Craig Knoblock, Pedro Szekely and José Luis Ambite",Taheriyan,Leveraging Linked Data to Discover Semantic Relations within Data Sources,research,Enriching Data Sources,2,Mohsen Taheriyan,research_107.pdf,502,2016-10-21T15:50:00,2016-10-21T16:10:00,"Mapping data to a shared domain ontology is a key step in publishing semantic content on the Web. Most of the work on automatically mapping structured and semi-structured sources to ontologies focuses on semantic labeling, i.e., annotating data fields with ontology classes and/or properties. However, a precise mapping that fully recovers the intended meaning of the data needs to describe the semantic relations between the data fields too. We present a novel approach to automatically discover the semantic relations within a given data source. We mine the small graph patterns occurring in Linked Open Data and combine them to build a graph that will be used to infer semantic relations. We evaluated our approach on datasets from different domains. Mining patterns of maximum length five, our method achieves an average precision of 75% and recall of 77% for a dataset with very complex mappings to the domain ontology, increasing up to 86% and 82%, respectively, for simpler ontologies and mappings."
  demo_115,115,Wouter Beek and Jan Wielemaker,Beek,SWISH: An Integrated Semantic Web Notebook,demo,Poster and Demo session,3,Wouter Beek,demo_115.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,SPARQL editors make it easier to write and inspect their results. Notebooks already support computer- and data scientists in domains like statistics and machine learning. There is currently not an integrated notebook solution for Semantic Web (SW) programming that combines the strengths of SPARQL editors with the benefits of notebooks. SWISH gives an integrated notebook experience for the Semantic Web programmer.
  demo_108,108,"Mihael Arcan, Mauro Dragoni and Paul Buitelaar",Arcan,The ESSOT System Goes Wild: an Easy Way For Translating Ontologies,demo,Poster and Demo session,12,Mihael Arcan,demo_108.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"To enable knowledge access across languages, ontologies that are often represented only in English, need to be translated into different languages.
  Since manual multilingual enhancement of domain-specific ontologies is very time consuming and expensive, smart solutions are required to facilitate the translation task for the language and domain experts.
  For this reason, we present ESSOT, an Expert Supporting System for Ontology Translation, which support experts in accomplishing the multilingual ontology management task. Differently than the classic document translation, ontology label translation faces highly specific vocabulary and lack contextual information. 
  Therefore, ESSOT takes advantage of the semantic information of the ontology for translation improvement of the ontology labels."
  research_68,68,"Giuseppe De Giacomo, Xavier Oriol, Riccardo Rosati and Domenico Fabio Savo",Giacomo,Updating DL-Lite Ontologies through First-Order Queries,research,Reasoning,2,Giuseppe De Giacomo,research_68.pdf,504+505,2016-10-21T15:50:00,2016-10-21T16:10:00,"In this paper we study instance-level update in DL-LiteA, the description logic underlying the OWL 2 QL standard. In particular we focus on formula based approaches to ABox insertion and deletion. We show that DL-LiteA, which is well known for enjoying first-order rewritability of query answering, enjoys a first-order rewritability property also for updates. That is, every update can be reformulated into a set of insertion and deletion instructions computable through a non-recursive DATALOG program. Such a program is readily translatable into a first-order query over the ABox considered as a database, and hence into SQL. Exploiting this result we implement an update component for DL-LiteA-based systems and perform some experiments showing that the approach works in practice."
  demo_105,105,"Shuya Abe, Yutaka Mitsuishi, Shinichiro Tago, Nobuyuki Igata, Seiji Okajima, Hiroaki Morikawa and Fumihito Nishino",Abe,Linked Corporations Data in Japan,demo,Poster and Demo session,13,Shuya Abe,demo_105.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Based on Open Data Charter of G8, the governments are publishing corporation register data as Open Data. In Japan, the government recently published a dataset covering approximately 4.4 million corporations, but the dataset is rated as 3 star in the 5-star rating system. Our policy, which we believe is also common in the LOD community, is that low-star datasets must be converted into 5 star as early as possible for strengthening the power of LOD. Based on this policy, we designed a schema for corporation data, converted the Japanese dataset into 5 star using this schema, and published this dataset under Creative Commons Attribution 4.0 License on 9th December 2015, only eight days after the publication date of the original dataset. As far as we know, eight datasets currently refer to ours, which makes the degree of 5 star stronger. As a business purpose, we internally appended links between our dataset and other data such as DBpedia, and applied this enriched data to a visualization system for browsing a corporation from various perspectives."
  demo_102,102,"Tabea Tietz, Jörg Waitelonis, Joscha Jäger and Harald Sack",Tietz,refer: a Linked Data based Text Annotation and Recommender System for Wordpress,demo,Poster and Demo session,14,Tabea Tietz,demo_102.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"When searching for an arbitrary subject in weblogs or archives, users often don’t get the information they are really looking for. Often they are overwhelmed with an overflow of information while sometimes the presented information is too scarce to make any use of it. Without further knowledge about the context or background of the intended subject users are easily frustrated because they either cannot handle the amount of information or they might give up because they cannot make sense of the topic at all. Furthermore, authors of online-platforms often deal with the issue to provide useful recommendations of other articles and to motivate the readers to stay on the platform to explore more of the available but most times hidden content of their blog or archive.
  In the demo presentation, we present refer, a semantic annotation and visualization system integrated into the Wordpress platform. With refer, content creators are enabled to (semi-)automatically annotate their texts with DBpedia resources as part of the original writing process and visualize them automatically. With refer users are encouraged to take an active part in discovering a platform’s information content interactively and intuitively, rather than just to have to read the entire textual information provided by the author. They can discover background information as well as relationships among persons, places, events, and anything related to the subject in current focus and are inspired to navigate the previously hidden information on a platform.
  "
  application_15,15,"Vanessa Lopez, Pierpaolo Tommasi, Spyros Kotoulas and Jiewen Wu",Lopez,QuerioDALI: Question Answering over Dynamic and Linked Knowledge Graphs,application,Medical Applications,3,Vanessa Lopez,application_15.pdf,501,2016-10-21T14:10:00,2016-10-21T14:30:00,"We present a domain-agnostic system for Question Answering over multiple semi-structured and possibly linked datasets without the need of a training corpus. The system is motivated by an industry use-case where Enterprise Data needs to be combined with a large body of Open Data to fulfill information needs not satisfied by prescribed application data models. Our proposed Question Answering pipeline combines existing components with novel methods to perform, in turn, linguistic analysis of a query, named entity extraction, entity / graph search, fusion and ranking of possible answers. We evaluate QuerioDALI with two open-domain benchmarks and a biomedical one over Linked Open Data sources, and show that our system produces comparable results to systems that require training data and are domain-dependent. In addition, we analyze the current challenges and shortcomings."
  application_13,13,"Evgeny Kharlamov, Bernardo Cuenca Grau, Ernesto Jimenez-Ruiz, Steffen Lamparter, Gulnar Mehdi, Martin Ringsquandl, Yavor Nenov, Sebastian Brandt and Ian Horrocks",Kharlamov,Capturing Industrial Information Models with Ontologies and Constraints,application,Ontologies (I),2,Evgeny Kharlamov,application_13.pdf,501,2016-10-20T15:50:00,2016-10-20T16:10:00,"This paper describes the outcomes of an ongoing collaboration between Siemens and the University of Oxford, with the goal of facilitating the design of ontologies and their deployment in applications. Ontologies are mainly used in Siemens to capture the conceptual information models underpinning a wide range of applications. We start by describing the key role that such models play in two use cases in the manufacturing and energy production sectors. Then, we discuss the formalisation of information models using ontologies, and the relevant reasoning services. Finally, we present SOMM---a tool that supports engineers with little background on semantic technologies in the creation of ontology-based models and in populating them with data. SOMM implements a fragment of OWL 2 RL extended with a form of integrity constraints for data validation, and it comes with support for schema and data reasoning, as well as for model integration. Our evaluation demonstrates the adequacy of SOMM's functionality and performance for Siemens applications."
  application_10,10,"Robert Piro, Ian Horrocks, Peter Hendler, Yavor Nenov, Boris Motik, Michael Rossman and Scott Kimberly",Piro,Semantic Technologies for Data Analysis in Health Care,application,Medical Applications,4,Robert Piro,application_10.pdf,501,2016-10-21T14:30:00,2016-10-21T14:50:00,"One focus of Semantic Technologies are formalisms that allow to express complex properties of and relationships between classes of data. The declarative nature of these formalisms is close to natural language and human conceptualisation and thus Semantic Technologies enjoy increasing popularity in scenarios where traditional solutions lead to very convoluted procedures which are difficult to maintain and whose correctness is difficult to judge.
  A fruitful application of Semantic Technologies in the field of health care data analysis has emerged from the collaboration between Oxford and Kaiser Permanente a US health care provider (HMO). US HMOs have to annually deliver measurement results on their quality of care to US authorities. One of these sets of measurements is defined in a specification called HEDIS which is infamous amongst data analysts for its complexity. Traditional solutions with either SAS-programs or SQL-queries lead to involved solutions whose maintenance and validation is difficult and binds considerable amount of resources.
  In this paper we present the project in which we have applied Semantic Technologies to compute the most difficult part of the HEDIS measures. We show that we arrive at a clean, structured and legible encoding of HEDIS in the rule language of the RDF-triple store RDFox. We use RDFox's reasoning capabilities and SPARQL queries to compute and extract the results. The results of a whole Kaiser Permanente regional branch could be computed in competitive time by RDFox on readily available commodity hardware. Further development and deployment of the project results are envisaged in Kaiser Permanente."
  application_18,18,"Evgeny Kharlamov, Yannis Kotidis, Theofilos Mailis, Christian Neuenstadt, Charalampos Nikolaou, Özgür Lütfü Özcep, Christoforos Svingos, Dmitriy Zheleznyakov, Steffen Lamparter, Ian Horrocks, Yannis Ioannidis and Ralf Möller",Kharlamov,Towards Analytics Aware Ontology Based Access to Static and Streaming Data,application,Ontologies (I),3,Evgeny Kharlamov,application_18.pdf,501,2016-10-20T16:10:00,2016-10-20T16:30:00,"Real-time analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios such as diagnostics of turbines in Siemens. OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations in dealing with analytics that restrict its use in important industrial applications. Based on our experience with Siemens, we argue that in order to overcome those limitations OBDA should be extended and become analytics, source, and cost aware. In this work we propose such an extension. In particular, we propose an ontology, mapping, and query language for OBDA, where aggregate and other analytical functions are first class citizens. Moreover, we develop query optimisation techniques that allow to efficiently process analytical tasks over static and streaming data. We implement our approach in a system and evaluate our system with Siemens turbine data."
  poster_18,18,Hong Fang and Xiaowang Zhang,Fang,pSPARQL: A Querying Language for Probabilistic RDF (Extended Abstract),poster,Poster and Demo session,16,Hong Fang,poster_18.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this paper, we present a querying language for probabilistic RDF databases, where each triple has a probability, called pSRARQL, built on SPARQL, recommended by W3C as a querying language for RDF databases. Firstly, we present the syntax and semantics of pSPARQL. Secondly, we define the query problem of pSPARQL corresponding to probabilities of solutions. Finally, we show that the query evaluation of general pSPARQL patterns is PSPACE-complete."
  poster_19,19,Monika Solanki,Solanki,Enabling combined software and data engineering: the ALIGNED suite of ontologies,poster,Poster and Demo session,17,Monika Solanki,poster_19.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00," Effective, collaborative integration of software and big data
   engineering for Web-scale systems, is now a crucial technical and
   economic challenge. This requires new combined data and software
   engineering processes and tools. Semantic metadata standards and
   linked data principles, provide a technical grounding for such
   integrated systems given an appropriate model of the domain. In this
   paper we introduce the ALIGNED suite of ontologies specifically
   designed to model the information exchange needs of combined
   software and data engineering. The models have been deployed to
   enable: tool-chain integration, such as the exchange of data quality
   reports; cross-domain communication, such as interlinked data and
   software unit testing; mediation of the system design process
   through the capture of design intents and as a source of context for
   model-driven software engineering processes. These ontologies are
   deployed in web-scale, data-intensive, system development
   environments in both the commercial and academic domains. We
   exemplify the usage of the suite on a complex collaborative software
   and data engineering scenario from the legal information system
   domain."
  resource_13,13,"Laura M. Daniele, Monika Solanki, Frank Den Hartog and Jasper Roes",Daniele,Interoperability for Smart Appliances in the IoT World,resource,Smart Planet,4,Laura M. Daniele,resource_13.pdf,504+505,2016-10-19T15:00:00,2016-10-19T15:20:00,"Household appliances are set to become highly intelligent, smart and networked devices in the near future. Systematically deployed on the Internet of Things (IoT), they would be able to form complete energy consuming, producing, and managing ecosystems. Smart systems are technically very heterogeneous, and standardized interfaces on a sensor and device level are therefore needed. However, standardization in IoT has largely focused at the technical communication level, leading to a large number of different solutions based on various standards and protocols, with limited attention to the common semantics contained in the message data structures exchanged at the technical level. The Smart Appliance REFerence ontology (SAREF) is a shared model of consensus developed in close interaction with the industry and with the support of the European Commission. It is published as a technical specification by ETSI and provides an important contribution to achieve semantic interoperability for smart appliances. This paper builds on the success achieved in standardizing SAREF and presents SAREF4EE, an extension of SAREF. SAREF4EE has been created in collaboration with the EEBus and Energy@Home industry associations to interconnect their (different) data models. By using SAREF4EE, smart appliances from different manufacturers that support the EEBus or Energy@Home standards can easily communicate with each other using any energy management system at home or in the cloud."
  poster_49,49,"Sejin Chun, Jooik Jung, Xiongnan Jin, Seungjun Yoon and Kyong-Ho Lee",Chun,Proactive Replication of Dynamic Linked Data for Scalable RDF Stream Processing,poster,Poster and Demo session,48,Sejin Chun,poster_49.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this paper, we propose a proactive replication of Linked Data for RDF Stream Processing. Our solution achieves a fast query processing by replicating subsets of remote RDF datasets before query evaluation. To construct the replication process effectively, we present an update estimation model to handle the changes in updates over time. With the update estimation model, we re-compose instances of the replication process in response to some problems, i.e., the outdated data.
  Finally, we conduct exhaustive tests with a real-world dataset to verify
  our solution."
  poster_10,10,"Terue Takatsuki, Mikako Saito, Sadahiro Kumagai, Eiki Takayama, Kazuya Ohshima, Nozomu Ohshiro, Kai Lenz, Nobuhiko Tanaka, Norio Kobayashi and Hiroshi Masuya",Takatsuki,A RDF based Portal of Biological Phenotype Data produced in Japan,poster,Poster and Demo session,18,Terue Takatsuki,poster_10.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"We developed RDF-based databases of phenotype and animal strains produced in Japan and a portal site termed as “J-Phenome”. By the application of common schema, these databases can be retrieved by the same SPARQL query across graphs. In the operation of these databases, RDF represented multiple advantages such as improvement of comprehensive search, data integration using ontologies and public data, reuse of data and wider dissemination of phenotype data compared to conventional technologies."
  poster_11,11,"Masao Watanabe, Kazunari Hashimoto, Seiya Inagi, Yohei Yamane, Seiji Suzuki and Hiroshi Umemoto",Watanabe,Working process quantification in factory using wearable sensor device and ontology-based stream data processing,poster,Poster and Demo session,19,Masao Watanabe,poster_11.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"A method for quantifying working processes on manufacturing floors was established that uses a wearable sensor device and an ontology-based stream data processing system.
  Using this method, the measurement of manufacturing process efficiency from sensor data extracted from such a device worn by workers on the job was confirmed at the Fuji Xerox factory."
  resource_18,18,"Ivan Ermilov, Jens Lehmann, Michael Martin and Sören Auer",Ermilov,LODStats: The Data Web Census Dataset,resource,Linked Data Measurement,3,Ivan Ermilov,resource_18.pdf,504+505,2016-10-20T14:10:00,2016-10-20T14:30:00,"Over the past years, the size of the Data Web has increased significantly, which makes obtaining general insights into its growth and structure both more challenging and more desirable. The lack of such insights hinders important data management tasks such as quality, privacy and coverage analysis. In this paper, we present LODStats, which provides a comprehensive picture of the current state of a significant part of the Data Web. LODStats integrates RDF datasets from data.gov, publicdata.eu and datahub.io data catalogs and at the time of writing lists over 9 000 RDF datasets. For each RDF dataset, LODStats collects comprehensive statistics and makes these available in adhering to the LDSO vocabulary. This analysis has been regularly published and enhanced over the past four years at the public platform lodstats.aksw.org. We give a comprehensive overview over the resulting dataset."
  poster_14,14,"Christophe Debruyne, Eamonn Clinton, Lorraine McNerney, Atul Nautiyal and Declan O'Sullivan",Debruyne,Serving Ireland's Geospatial Information as Linked Data,poster,Poster and Demo session,21,Christophe Debruyne,poster_14.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this paper we present data.geohive.ie, which aims to serve Ireland’s national geospatial data as authoritative Linked Data. Currently, the platform provides information on Irish administrative boundaries and the platform was designed to support two use cases: serving boundary data of geographic features at various level of detail and capturing the evolution of administrative boundaries. We report on the decisions taken for modeling and serving the information such as the adoption of an appropriate URI strategy, the devel-opment of necessary ontologies, and the use of (named) graphs to support the aforementioned use cases. "
  research_177,177,"Freddy Brasileiro, Joao Paulo Almeida, Victorio Albani Carvalho and Giancarlo Guizzardi",Brasileiro,Expressive Multi-Level Modeling for the Semantic Web,research,Knowledge Representation,4,Freddy Brasileiro,research_177.pdf,502,2016-10-19T12:00:00,2016-10-19T12:20:00,"In several subject domains, classes themselves may be subject to categorization, resulting in classes of classes (or “metaclasses”). When representing these do-mains, one needs to capture not only entities of different classification levels, but also their (intricate) relations. We observe that this is challenging in current Se-mantic Web languages as there is little support to guide the modeler in producing correct multi-level ontologies, especially because of the nuances in the constraints that apply to entities of different classification levels and their relations. In order to address these representation challenges, we propose a vocabulary that can be used as a basis for multi-level ontologies in OWL along with a number of integri-ty constraints to prevent the construction of inconsistent models. In this process we employ an axiomatic theory called MLT (a Multi-Level Modeling Theory)."
  poster_40,40,"Junzhao Zhang, Xiaowang Zhang and Zhiyong Feng",Zhang,IRSMG: Accelerating Inexact RDF Subgraph Matching on the GPU,poster,Poster and Demo session,46,Junzhao Zhang,poster_40.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Many existing approaches have been proposed to solve subgraph matching problem based on filter-and-refine strategy. The efficiency of those existing serial approaches relies on the computational capabilities of CPU. In this paper, we propose an RDF subgraph matching algorithm based on type-isomorphism using GPU since GPU has higher computational performance, more scalability, and lower price than CPU. Firstly, we present a concurrent matching model for type-isomorphism so that subgraph matching can be tackled in a parallel way. Secondly, we develop a parallel algorithm for capturing our proposed concurrent matching model and implement a prototype called IRSMG using GPU. Finally, we evaluate IRSMG on the benchmark datasets LUBM. The experiments show that IRSMG significantly outperforms the state-of-the-art algorithms on the CPU."
  research_270,270,"Linhong Zhu, Majid Ghasemi-Gol, Pedro Szekely, Aram Galstyan and Craig Knoblock",Zhu,Unsupervised Entity Resolution on Multi-type Graphs,research,Ontology Matching,4,Linhong Zhu,research_270.pdf,502,2016-10-20T11:30:00,2016-10-20T11:50:00,"We address the problem of performing entity resolution on RDF graphs containing multiple types of nodes, using the links between instances of different types to improve the accuracy. For example, in a graph of products and manufacturers the goal is to resolve all the products and all the manufacturers. We formulate this problem as multi-type graph summarization problem, which involves clustering the nodes in each type that refer to the same entity into one super node and creating weighted links among super nodes that summarize the inter-cluster links in the original graph. Experiments show that the proposed approach outperforms several state-of-the-art generic entity resolution approaches, especially in data sets with one-to-many, many-to-many relations and attributes with missing values."
  demo_59,59,"Freddy Lecue, John Vard and Jiewen Wu",Lecue,Using Semantic Web Technologies for Explaining and Predicting Abnormal Expense,demo,Poster and Demo session,32,Freddy Lecue,demo_59.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Travel expenses represent up to 7% of organizations overall budget. Existing expenses systems are designed for reporting expenses types and amount, but not for understanding how to save and spend. We present a system, manipulating semantic web technologies, which aims at identifying, explaining, predicting abnormal expense claims by employees of large organizations in 500+ cities."
  demo_112,112,"Michel Buffa, Catherine Faron Zucker, Thierry Bergeron and Hatim Aouzal",Buffa,"Semantic Web Technologies for improving remote visits of museums, using a mobile robot",demo,Poster and Demo session,15,Michel Buffa,demo_112.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"The Azkar research project focuses on the remote control of a mobile robot using the emerging Web technologies WebRTC for real time communication. One of the use cases addressed is a remote visit of the French Museum of the Great War in Meaux. For this purpose, we designed an ontology for describing the main scenes in the museum, the objects that compose them, the different trails the robot can follow in a given time period, for a targeted audience, the way points, observation points. This RDF dataset is exploited to assist the human guide in designing a trail, and possibly adapting it during the visit. In this paper we present the Azkar Museum Ontology, the RDF dataset describing some emblematic scenes of the museum, and an experiment that took place in June 2016 with a robot controlled by an operator located 800~kms from the museum. We propose to demonstrate this work in real time during the conference by organizing a remote visit from the conference demo location."
  research_78,78,"Imen Megdiche, Olivier Teste and Cassia Trojahn",Megdiche,An Extensible Linear Approach For Holistic Ontology Matching,research,Ontology Matching,2,Imen Megdiche,research_78.pdf,502,2016-10-20T10:50:00,2016-10-20T11:10:00,"Resolving the semantic heterogeneity in the semantic web requires finding correspondences between ontologies describing resources. In particular, with the explosive growth of data sets in the Linked Open Data, linking multiple vocabularies and ontologies simultaneously, known as holistic matching problem, become necessary. Currently, most state-of-the-art matching approaches are limited to pairwise matching. In this paper, we propose an approach for holistic ontology matching that is modeled through a linear program extending the maximum-weighted graph matching problem with linear constraints (cardinality, structural, and coherence constraints). Our approach guarantees the optimal solution with mostly coherent alignments. To evaluate our proposal, we discuss the results of experiments performed on the Conference track of the OAEI 2015, under both holistic and pairwise matching settings."
  poster_17,17,"Zhenyu Song, Xiaowang Zhang and Zhiyong Feng",Song,PRONA: A Plugin for Well-Designed Approximate Queries in Jena,poster,Poster and Demo session,20,Zhenyu Song,poster_17.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"The time of answering a SPARQL query with its all exact solutions in large scale RDF dataset possibly exceeds users' tolerable waiting time, especially when it contains the OPT operations since the OPT operation is the least conventional operator in SPARQL.
  It becomes essential to make a trade-off between the query response time and solution accuracy. We propose PRONA - an plugin for well-designed approximate queries in Jena, which provides help for users to answer well-designed SPARQL queries by approximate computation.The main features of PRONA comprise SPARQL query engine with approximate queries, as well as various approximate degrees for users to choose."
  doctoralconsortium_24,24,Syed Muhammad Ali Hasnain,Hasnain,A - Posteriori Data Integration for Life Sciences,doctoralconsortium,Session 1,3,Syed Muhammad Ali Hasnain,doctoralconsortium_24.pdf,,2016-10-18T11:30:00,2016-10-18T11:45:00,"Multiple datasets that add high value to biomedical research have been exposed on the web as part of the Life Sciences Linked Open Data (LS-LOD) Cloud. The ability to easily navigate through these datasets is crucial in order to draw meaningful biological co relations. However, navigating these multiple datasets is not trivial as most of these are only available as isolated SPARQL endpoints with very little vocabulary reuse. We propose an approach for Autonomous Resource Discovery and Indexing (ARDI), a set of configurable rules which can be used to discover links between biological entities in the LS-LOD cloud. We have catalogued and linked concepts and properties from 137 public SPARQL endpoints. The ARDI is used to dynamically assemble queries retrieving data from multiple SPARQL endpoints simultaneously."
  poster_15,15,"Makoto Urakawa, Masaru Miyazaki, Hiroshi Fujisawa, Masahide Naemura and Ichiro Yamada",Urakawa,Constructing Curriculum Ontology and Dynamic Learning Path Based on Resource Description Framework,poster,Poster and Demo session,22,Makoto Urakawa,poster_15.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Curriculum for school is generated based on the academic year. For the reason that students need to learn many subjects every year, the relative topics are put into curricula in discrete. In this study, we propose a method to construct a dynamic learning path which enables us to learn the relative topics continuously. In this process, we define two kinds of similarity score, inheritance score and context similarity score to connect the learning path of relative topics. We also construct curriculum ontology with Resource Description Framework (RDF) to make the dynamic learning path accessible. Using the curriculum ontology, we develop a learning system for school which shows a dynamic learning path with broadcasted video clips."
  doctoralconsortium_21,21,Takeshi Masuda,Masuda,Ontology Refinement and Evaluation System based on Similarity of Is-a Hierarchies,doctoralconsortium,Session 3,1,Takeshi Masuda,doctoralconsortium_21.pdf,,2016-10-18T16:00:00,2016-10-18T16:15:00,"Ontologies are constructed in various fields such as medical information, mechanical design, and etc. It is important to build high quality ontologies so that these ontologies are used as knowledge bases and knowledge models for application systems. However it is hard to build good quality ontologies because of the necessity of both knowledge of ontology and expertise in their target domain. For this background, ontology construction and refinement costs a lot of time and ef-fort. In order to reduce such costs, we develop an ontology refinement support system. This system have two main function. First, the system can detect points that should be refined and propose how to refine it. Second, the system can evaluate ontologies quantitatively. This system indicate how ontologies are consistent in a classificatory criterion. To develop the refinement support system, we focus on a guideline for building well-organized ontologies that “Each subclass of a super class is distinguished by the values of exactly one attribute of the super class”. When an ontology is built following this guideline, there is similarity among Is-a hierarchies. We use these similar Is-a hierarchies and develop an ontology refinement system."
  doctoralconsortium_20,20,Xiangnan Ren,Ren,"Towards a distributed, scalable and real-time RDF Stream Processing engine",doctoralconsortium,Session 2,4,Xiangnan Ren,doctoralconsortium_20.pdf,,2016-10-18T14:45:00,2016-10-18T15:00:00,"Due to the growing need to timely process and derive valuable information and knowledge from data produced in the Semantic Web, RDF stream processing (RSP) has emerged as an important research domain. Of course, modern RSP have to address the volume and velocity characteristics encountered in the Big Data era. This comes at the price of designing high throughput, low latency, fault tolerant, highly available and scalable engines. The cost of implementing such systems from scratch is very high and usually one prefers to program components on top of a framework that possesses these properties, e.g., Apache Hadoop or Apache Spark. The research conducting in this PhD adopts this approach and aims to create a production-ready RSP engine which will be based on domain standards, e.g., Apache Kafka and Spark Streaming. In a nutshell, the engine aims to i) address basic event modeling - to guarantee the completeness of input data in window operators, ii) process real-time RDF stream in a distributed manner - efficient RDF stream handling is required; iii) support and extend common continuous SPARQL syntax - easy-to-use, adapt to the industrial needs and iv) support reasoning services at both the data preparation and query processing levels."
  doctoralconsortium_23,23,Sebastian Neumaier,Neumaier,Improving Open Data Usability through Semantics,doctoralconsortium,Session 3,3,Sebastian Neumaier,doctoralconsortium_23.pdf,,2016-10-18T16:30:00,2016-10-18T16:45:00,"With the success of Open Data a huge amount of tabular data become available that could potentially be mapped and linked into the Web of (Linked) Data. The use of semantic web technologies would then allow to explore related content and enhanced search functionalities across data portals. However, existing linkage and labeling approaches mainly rely on mappings of textual information to classes or properties in knowledge bases. In this work we outline methods to recover the semantics of tabular Open Data and to identify related content which allows a mapping and automated integration/categorization of Open Data resources and improves the overall usability and quality of Open Data."
  demo_83,83,"Md. Kamruzzaman Sarker, Adila A. Krisnadhi and Pascal Hitzler",Sarker,OWLAx: A Protege Plugin to Support Ontology Axiomatization through Diagramming,demo,Poster and Demo session,41,Md. Kamruzzaman Sarker,demo_83.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Once the conceptual overview, in terms of a somewhat informal class diagram, has been designed in the course of engineering an ontology, the process of adding many of the appropriate logical axioms is mostly a routine task. We provide a Protege plugin which supports this task, together with a visual user interface, based on established methods for ontology design pattern modeling."
  poster_28,28,Paolo Pareti,Pareti,Human-Machine Collaboration over Linked Data,poster,Poster and Demo session,24,Paolo Pareti,poster_28.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,This study presents a framework to allow human and machine agents to reason and coordinate actions without direct communication mechanisms by sharing distributed Linked Data resources. This framework addresses the problems of querying frequently-updating distributed datasets and guaranteeing transactional consistency. The motivation for this framework comes from the use-case of opportunistic automation of humans-generated procedures. This use-case is based on existing real-world Linked Data representations of human instructions and their integration with machine functionalities.
  research_163,163,"Victor Christen, Anika Groß and Erhard Rahm",Christen,A Reuse-based Annotation Approach for Medical Documents,research,Medical Applications,2,Victor Christen,research_163.pdf,501,2016-10-21T13:50:00,2016-10-21T14:10:00,"Annotations are useful to semantically enrich documents and other datasets with concepts of standardized vocabularies and ontologies. In the medical domain, many documents are not annotated at all and manual annotation is a difficult and time-consuming process. Therefore, automatic annotation methods become necessary to support human annotators with recommendations. We propose a reuse-based annotation approach that clusters items in medical documents according to verified ontology-based annotations. We identify a set of representative features for annotation clusters and propose a context-based selection strategy that considers the semantic relatedness and frequent co-occurrences of annotated concepts. We evaluate our methods and the annotation tool MetaMap based on reference mappings between medical forms and the Unified Medical Language System."
  research_167,167,"Ilaria Tiddi, Mathieu d'Aquin and Enrico Motta",Tiddi,Learning to Assess Linked Data Relationships Using Genetic Programming,research,Linked Data Measurement,2,Ilaria Tiddi,research_167.pdf,504+505,2016-10-20T13:50:00,2016-10-20T14:10:00,"The goal of this work is to learn a measure supporting the detection of strong relationships between Linked Data entities. Such relationships can be represented as paths of entities and properties, and can be obtained through a blind graph search process traversing Linked Data. The challenge here is therefore the design of a cost-function that is able to detect the strongest relationship between two given entities, by objectively assessing the value of a given path. To achieve this, we use a Genetic Programming approach in a supervised learning method to generate path evaluation functions that compare well with human evaluations. We show how such a cost-function can be generated only using basic topological features of the nodes of the paths as they are being traversed (i.e. without knowledge of the whole graph), and how it can be improved through introducing a very small amount of knowledge about the vocabularies of the properties that connect nodes in the graph."
  poster_21,21,Olaf Hartig and Carlos Buil Aranda,Hartig,Reducing the Network Load of Triple Pattern Fragments by Supporting Bind Joins,poster,Poster and Demo session,26,Olaf Hartig,poster_21.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"The recently proposed Triple Pattern Fragment (TPF) interface aims at increasing the availability of Web-queryable RDF datasets by trading off an increased client-side query processing effort for a significant reduction of server load. However, an additional aspect of this trade-off is a very high network load. To mitigate this drawback we propose to extend the interface by allowing clients to augment TPF requests with a VALUES clause as introduced in SPARQL 1.1. In an ongoing research project we study the trade-offs of such an extended TPF interface and compare it to the pure TPF interface. With a poster in the conference we aim to present initial results of this research. In particular, we would like to present a series of experiments showing that a distributed, bind-join-based query execution using this extended interface can reduce the network load drastically (in terms of both the number of HTTP requests and data transfer)."
  research_164,164,Olaf Hartig and M. Tamer Ozsu,Hartig,Walking without a Map: Ranking-Based Traversal for Querying Linked Data,research,Search (II),4,Olaf Hartig,research_164.pdf,504+505,2016-10-20T16:30:00,2016-10-20T16:50:00,"The emergence of Linked Data on the WWW has spawned research interest in an online execution of declarative queries over this data. A particularly interesting approach is traversal-based query execution which fetches data by traversing data links and, thus, is able to make use of up-to-date data from initially unknown data sources. While the downside of this approach is the delay before the query engine completes a query execution, user perceived response time may be improved significantly by returning as many elements of the result set as soon as possible. To this end, the query engine requires a traversal strategy that enables the engine to fetch result-relevant data as early as possible. The challenge for such a strategy is that the query engine does not know a priori what data sources will be discovered during the query execution and which of them contain result-relevant data. In this paper, we investigate 14 different approaches to rank traversal steps and achieve a variety of traversal strategies. We experimentally study their impact on response times and compare them to a baseline that resembles a breadth-first traversal. While our experiments show that some of the approaches can achieve noteworthy improvements over the baseline in a significant number of cases, we also observe that for every approach, there is a non-negligible chance to achieve response times that are worse than the baseline."
  research_242,242,"Bahaa Eldesouky, Menna Bakry, Heiko Maus and Andreas Dengel",Eldesouky,"Seed, an End-user Text Composition Tool for the Semantic Web",research,Interaction,1,Bahaa Eldesouky,research_242.pdf,504+505,2016-10-19T11:00:00,2016-10-19T11:20:00,"Despite developments of Semantic Web-enabling technologies,
  the gap between non-expert end-users and the Semantic Web still
  exists. In the field of semantic content authoring, tools for interacting
  with semantic content remain directed at highly trained individuals. This
  adds to the challenges of bringing user-generated content into the Semantic
  Web.
  In this paper, we present Seed, short for Semantic Editor, an extensible
  knowledge-supported natural language text composition tool, which
  targets non-experienced end-users enabling automatic as well as semiautomatic
  creation of standards based semantically annotated textual
  content. We point out the structure of Seed, compare it with related
  work and explain how it utilizes Linked Open Data and state of the art
  Natural Language Processing to realize user-friendly generation of textual
  content for the Semantic Web. We also present experimental evaluation
  results involving a diverse group of more than 120 participants,
  which showed that Seed helped end-users easily create and interact with
  semantic content with nearly no prerequisite knowledge."
  demo_54,54,Jędrzej Potoniec,Potoniec,An On-Line Learning to Query System,demo,Poster and Demo session,28,Jędrzej Potoniec,demo_54.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,We present an on-line system which learns a SPARQL query from a set of wanted and a set of unwanted results of the query. The sets are extended during a dialog with the user. The system leverages SPARQL 1.1 and does not depend on any particular RDF graph.
  resource_81,81,"Efstratios Sygkounas, Giuseppe Rizzo and Raphaël Troncy",Sygkounas,A Replication Study of the Top Performing Systems in SemEval Twitter Sentiment Analysis,resource,Natural Language Processing,3,Efstratios Sygkounas,resource_81.pdf,504+505,2016-10-21T11:10:00,2016-10-21T11:30:00,"We performed a thorough replicate study of the top systems performing in the yearly SemEval Twitter Sentiment Analysis task. We highlight some differences between the results obtained by the top systems and the ones we are able to compute. We also propose SentiME, an ensemble system composed of 5 state-of-the-art sentiment classifiers. SentiME first trains the different classifiers using the Bootstrap Aggregating Algorithm. The classification results are then aggregated using a linear function that averages the classification distributions of the different classifiers. SentiME has also been tested over the SemEval2015 test set, properly trained with the SemEval2015 train test, outperforming the best ranked system of the challenge.
  
  "
  demo_52,52,"Michel Héon, Roger Nkambou and Mohamed Gaha",Héon,OntoCASE4G-OWL: Towards a modeling software tool for G-OWL a visual syntax for RDF/RDFS/OWL2,demo,Poster and Demo session,29,Michel Héon,demo_52.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Ontological syntax standardized by the W3C offer the expressiveness needed in the formulation of complex concepts. However, the codification of an ontology is a process of formalization of thought that sometimes requires extensive knowledge and is often inaccessible in the layperson's logic. The G-OWL (for Graphical OWL) language has been designed to provide a tool to facilitate the expression of knowledge in a manner that is compatible with the OWL2 ontolo-gy. This paper presents the OntoCASE4G-OWL prototype, a visual modeling software for the editing of formal ontologies in G-OWL and their translation into Turtle. The executable version of OntoCASE for Windows and MacOsX is available at http://www.cotechnoe.com/iswc2016"
  resource_87,87,"Alberto Tonon, Djellel Eddine Difallah, Victor Felder and Philippe Cudré-Mauroux",Tonon,VoldemortKG: Mapping Schema.org Entities to Linked Open Data,resource,Knowledge Graph,1,Alberto Tonon,resource_87.pdf,501,2016-10-19T11:00:00,2016-10-19T11:20:00,"Increasingly, Web pages mix entities coming from different sources and represented in several different ways. It can thus happen that the same entity is both described by using schema.org annotations and by creating a text anchor pointing to its Wikipedia page. Often, those representations provide complementary information which is not exploited since those entities are disjoint.
  
  In this project, we explore the extent to which entities represented in different ways repeat on the Web, how they are related, and how they complement (or link) to each other. Our initial experiments show that we can unveil a previously (unexploited) knowledge graph by applying simple instance matching techniques on a large collection of schema.org annotations and DBpedia. The resulting knowledge graph aggregates entities (often tail entities) scattered across several Web pages, and complements existing DBpedia entities with new facts and properties.
  
  In order to facilitate further investigations in how to mine such information, we are releasing i) an excerpt of all CommonCrawl web pages containing both Wikipedia and schema.org annotations, ii) the toolset to extract this information and perform knowledge graph construction and mapping onto DBpedia, as well as iii) the resulting knowledge graph (VoldemortKG) obtained via label matching techniques."
  resource_88,88,"Vincent Link, Steffen Lohmann and Florian Haag",Link,OntoBench: Generating Custom OWL 2 Benchmark Ontologies,resource,Reasoning,4,Vincent Link,resource_88.pdf,504+505,2016-10-21T16:30:00,2016-10-21T16:50:00,"A variety of tools for visualizing, editing, and documenting OWL ontologies have been developed in the last couple of years. The OWL coverage and conformance of these tools usually needs to be tested during development or for evaluation and comparison purposes. However, in particular for the testing of special OWL concepts and concept combinations, it can be tedious to find suitable ontologies and test cases. We have developed OntoBench, a generator for OWL 2 benchmark ontologies that can be used to test and compare ontology visualizers and related tools. In contrast to existing OWL benchmarks, OntoBench does not focus on scalability and performance but OWL coverage and concept combinations. Consistent benchmark ontologies are dynamically generated based on OWL 2 language constructs selected in a graphical user interface. OntoBench is available on GitHub and as a public service, making it easy to use the tool and generate custom ontologies or ontology fragments."
  poster_4,4,"Paramita Mirza, Simon Razniewski and Werner Nutt",Mirza,"Expanding Wikidata's Parenthood Information by 178%, or How To Mine Relation Cardinality Information",poster,Poster and Demo session,30,Paramita Mirza,poster_4.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"While automated knowledge base construction so far has largely focused on fully qualified facts, e.g. <Obama, hasChild, Malia>, the Web contains also extensive amounts of cardinality information, such as that someone has two children without giving their names. In this paper we argue that the extraction of such information could substantially increase the scope of knowledge bases. For the sample of the hasChild relation in Wikidata, we show that simple regular-expression based extraction from Wikipedia can increase the size of the relation by 178. We also show how such cardinality information can be used to estimate the recall of knowledge bases."
  demo_58,58,"Stefano Faralli, Christian Bizer, Kai Eckert, Robert Meusel and Simone Paolo Ponzetto",Faralli,A Web Application to Search a Large Repository of Taxonomic Relations from the Web,demo,Poster and Demo session,31,Stefano Faralli,demo_58.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Taxonomic relations (also known as ``isa'' relations or hypernymy relations) represent a fundamental atomic piece of structured information for many text understanding applications. Such structured information is part of the basic topology structure of knowledge bases and foundational ontologies. Despite the availability of shared knowledge bases, some NLP applications (e.g. Ontology Learning) require automatic isa relation harvesting techniques to cope with the coverage of domain-specific and long-tail terms. We present a Web Application to directly query our repository of isa relations extracted from the Common Crawl (the largest publicly available crawl of the Web). Our resource can be also downloaded for research purposes and accessed programmatically (we also release a Java application programming interface). "
  poster_7,7,Khai Nguyen and Ryutaro Ichise,Nguyen,Ranking Feature for Classifier-based Instance Matching,poster,Poster and Demo session,23,Khai Nguyen,poster_7.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Instance matching is the problem of finding the instances that describe the same object. It can be viewed as a classification problem, where a pair of two instances is predicted as match or non-match. A common limitation of existing classifier-based matching systems is the absent of instance pairs ranking.
  We propose using a ranking feature to enhance the classifier in instance matching. 
  Experiments on real datasets confirm the significant improvement when applying our method."
  journal_7,7,"John P. McCrae, Mihael Arcan, Kartik Asooja, Jorge Gracia, Paul Buitelaar and Philipp Cimiano",McCrae,Domain Adaptation for Ontology Localization,journal,Multilinguality,4,John P. McCrae,journal_7.pdf,501,2016-10-19T15:00:00,2016-10-19T15:20:00,"Ontology localization is the task of adapting an ontology to a different cultural context, and has been identified as an important task in the context of the Multilingual Semantic Web vision. The key task in ontology localization is translating the lexical layer of an ontology, i.e., its labels, into some foreign language. For this task, we hypothesize that the translation quality can be improved by adapting a machine translation system to the domain of the ontology. To this end, we build on the success of existing statistical machine translation (SMT) approaches, and investigate the impact of different domain adaptation techniques on the task. In particular, we investigate three techniques: (i) enriching a phrase table by domain-specific translation candidates acquired from existing Web resources, (ii) relying on Explicit Semantic Analysis as an additional technique for scoring a certain translation of a given source phrase, as well as (iii) adaptation of the language model by means of weighting n-grams with scores obtained from topic modelling. We present in detail the impact of each of these three techniques on the task of translating ontology labels. We show that these techniques have a generally positive effect on the quality of translation of the ontology and that, in combination, they provide a significant improvement in quality. "
  demo_77,77,"Matias Junemann, Juan L. Reutter, Adrian Soto and Domagoj Vrgoc",Junemann,Incorporating API data into SPARQL query answers,demo,Poster and Demo session,88,Matias Junemann,demo_77.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this demo we present an extension of SPARQL which allows queries to connect to JSON APIs and integrate the obtained information into query answers. We achieve this by adding a new operator to SPARQL, and implement this extension on top of the Jena framework in order to illustrate how it functions with real world APIs."
  poster_44,44,"Lihua Zhao, Naoya Arakawa, Hiroaki Wagatsuma and Ryutaro Ichise",Zhao,An Ontology based Map Converter for Intelligent Vehicles,poster,Poster and Demo session,44,Lihua Zhao,poster_44.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Sophisticated digital map is an essential resource for intelligent vehicles to localize and retrieve environment information. However, the open map source do not contain enough information for decision making during autonomous driving. Although comprehensive commercial map data can provide precise map knowledge, the data format is not in a machine-readable format. Therefore, we retrieve useful knowledge from high-precision commercial map and convert it into ontology based data to help intelligent vehicles perceive driving environment and make decisions at various traffic scenarios. Other than developing deci- sion making systems, the converted map data can be used as a golden standard for evaluating traffic sign detection, road mark detection, and automatic map construction."
  application_33,33,"Mihael Arcan, Mauro Dragoni and Paul Buitelaar",Arcan,Translating Ontologies in a Real-World Setting with ESSOT,application,Multilinguality,2,Mihael Arcan,application_33.pdf,501,2016-10-19T14:20:00,2016-10-19T14:40:00,"To enable knowledge access across languages, ontologies that are often represented only in English, need to be translated into different languages.
  The main challenge in translating ontologies is to find the right term with respect to the domain modeled by ontology itself.
  Machine translation services may help in this task; however, a crucial requirement is to have translations validated by experts before the ontologies are deployed.
  Real-world applications must implement a support system addressing this task for relieve experts work in validating all translations.
  