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: system performance and device resources depending on their availability. The
  adaptation model is based on the resource cost model of the data management
  techniques."
  doctoralconsortium_vander_sande_6,6,Miel Vander Sande,vander sande,Studying Metadata for better client-server trade-offs in Linked Data publishing,doctoralconsortium,Session 2,5,Miel Vander Sande,DC_VanderSande.pdf,,2016-10-18T09:00:00,2016-10-18T17:30:00,"Client-server trade-offs can be analyzed using Linked Data Fragments,
  which proposes an uniform view on all interfaces to rdf. This reveals a complete
  spectrum between Linked Data documents and the sparql protocol, in which
  we can advance the state-of-the-art of Linked Data publishing. This axis can be
  
negative.code: The peculiarity of this system is to exploit semantic information of the concept's context for improving the quality of label translations.
  The system has been tested both within the Organic.Lingua project by translating the modeled ontology in three languages and on other multilingual ontologies in order to evaluate the effectiveness of the system in other contexts.
  The results have been compared with the translations provided by the Microsoft Translator API and the improvements demonstrated the viability of the proposed approach."
  application_36,36,"Francesco Osborne, Angelo Salatino, Aliaksandr Birukou and Enrico Motta",Osborne,Automatic Classification of Springer Nature Proceedings with Smart Topic Miner,application,Data Mining,3,Francesco Osborne,application_36.pdf,502,2016-10-21T11:10:00,2016-10-21T11:30:00,"The process of classifying scholarly outputs is crucial to ensure timely access to knowledge. However, this process is typically carried out manually by expert editors, leading to high costs and slow throughput. In this paper we present Smart Topic Miner (STM), a novel solution which uses semantic web technologies to classify scholarly publications on the basis of a very large automatically generated ontology of research areas. STM was developed to support the Springer Nature Computer Science editorial team in classifying proceedings in the LNCS family. It analyses in real time a set of publications provided by an editor and produces a structured set of topics and a number of Springer Nature classification tags, which best characterise the given input. In this paper we present the architecture of the system and report on an evaluation study conducted with a team of Springer Nature editors. The results of the evaluation, which showed that STM classifies publications with a high degree of accuracy, are very encouraging and as a result we are currently discussing the required next steps to ensure large scale deployment within the company."
  application_38,38,"Kavitha Srinivas, Julian Dolby, Achille Fokoue, Mariano Rodríguez Muro and Wen Sun",Srinivas,Extending SPARQL for data analytic tasks,application,Querying/SPARQL (I),1,Kavitha Srinivas,application_38.pdf,501,2016-10-20T10:30:00,2016-10-20T10:50:00,"SPARQL has many nice features for accessing data integrated across different data sources, which is an important step in any data analysis task. We report the use of SPARQL for two real data analytic use cases from the healthcare and life sciences domains, which exposed certain weaknesses in the current specification of SPARQL; specifically when the data being integrated is most conveniently accessed via RESTful services and in formats beyond RDF, such as XML. We therefore extended SPARQL with generalized 'service', constructs for accessing services beyond the SPARQL endpoints supported by 'service'; for efficiency, our constructs additionally needed to support posting data, which is also not supported by 'service'. Furthermore, data from multiple sources led to natural modularity in the queries, with different portions of the query pertaining to different sources, so we also extended SPARQL with a simple 'function' mechanism to isolate the mechanics of accessing each endpoint. We provide an open source implementation of this SPARQL endpoint in an RDF store called Quetzal, and evaluate its use in the two data analytic scenarios over real datasets."
  poster_41,41,Fabien Gandon,Gandon,Materializing the editing history of Wikipedia as linked Data in DBpedia,poster,Poster and Demo session,45,Fabien Gandon,poster_41.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,We describe a DBpedia extractor materializing as linked data the editing history of Wikipedia pages to support historical queries and indicators.
  resource_73,73,"Amit Joshi, Pascal Hitzler and Guozhu Dong",Joshi,LinkGen: Multipurpose Linked Data Generator,resource,Linked Data,3,Amit Joshi,resource_73.pdf,504+505,2016-10-20T11:10:00,2016-10-20T11:30:00,"The paper presents a synthetic linked data generator that can generate a large amount of RDF data based on certain statistical distribution. Data generation is platform independent, supports streaming mode and produces output in N-Triples and N-Quad format. Different sets of output can be generated using various configuration parameters and the outputs are reproducible. Unlike existing generators, our generator accepts any vocabulary and can supplement the output with noisy and inconsistent data. The generator has an option to inter-link instances with real ones provided that the user supplies entities from real datasets."
  resource_25,25,"Andrea Giovanni Nuzzolese, Anna Lisa Gentile, Valentina Presutti and Aldo Gangemi",Nuzzolese,Conference Linked Data: the ScholarlyData project,resource,Linked Data,1,Andrea Giovanni Nuzzolese,resource_25.pdf,504+505,2016-10-20T10:30:00,2016-10-20T10:50:00,"The Semantic Web Dog Food (SWDF) is the reference linked dataset of the Semantic Web community about papers, people, organisations, and events related to its academic conferences. In this paper we analyse the existing problems of generating, representing and maintaining Linked Data for the SWDF. With this work (i) we provide a refactored and cleaned SWDF dataset; (ii) we use a novel data model which improves the Semantic Web Conference Ontology, adopting best ontology design practices and (iii) we provide an open source maintenance workflow to support a healthy grow of the dataset beyond the Semantic Web conferences."
  research_156,156,Petar Ristoski and Heiko Paulheim,Ristoski,RDF2Vec: RDF Graph Embeddings for Data Mining,research,Data Mining,2,Petar Ristoski,research_156.pdf,502,2016-10-21T10:50:00,2016-10-21T11:10:00,"Linked Open Data has been recognized as a valuable source for background information in data mining. However, most data mining tools require features in propositional form, i.e., a vector of nominal or numerical features associated with an instance, while Linked Open Data sources are graphs by nature. In this paper, we present RDF2Vec, an approach that uses language modeling approaches for unsupervised feature extraction from sequences of words, and adapts them to RDF graphs. We generate sequences by leveraging local information from graph sub-structures, harvested by Weisfeiler-Lehman Subtree RDF Graph Kernels and graph walks, and learn latent numerical representations of entities in RDF graphs. Our evaluation shows that such vector representations outperform existing techniques for the propositionalization of RDF graphs on a variety of different predictive machine learning tasks, and that feature vector representations of general knowledge graphs such as DBpedia and Wikidata can be easily reused for different tasks."
  research_88,88,Lei Zhang and Achim Rettinger,Zhang,A Probabilistic Model for Time-Aware Entity Recommendation,research,Search (I),4,Lei Zhang,research_88.pdf,502,2016-10-20T14:30:00,2016-10-20T14:50:00,"In recent years, there has been an increasing efforts to develop techniques for related entity recommendation, where the task is to retrieve a ranked list of related entities given a keyword query. Another trend in the area of information retrieval (IR) is to take temporal aspects of a given query into account when assessing the relevance of documents. However, while this has become an established functionality in document search engines, the significance of time, especially when explicitly given, has not been recognized for entity recommendation, yet. We address this gap by introducing the task of time-aware entity recommendation. We propose the first probabilistic model that takes time-awareness into consideration for entity recommendation by leveraging heterogeneous knowledge of entities extracted from different data sources publicly available on the Web. We extensively evaluate the proposed approach and our experimental results show considerable improvements compare to time-agnostic entity recommendation approaches."
  poster_43,43,"Xiang Nan 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 and Demo session,47,Xiang Nan Ren,poster_43.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"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. In this paper, we describe the design of an RSP engine that is built upon state of the art Big data frameworks, namely Apache Kafka and Apache Spark. Together, they support the implementation of a production-ready RSP engine that guarantees scalability, fault-tolerance, high availability, low latency and high throughput. Moreover, we highlight that the Spark framework considerably eases the implementation of complex applications requiring libraries as diverse as machine learning, graph processing, query processing and stream processing."
  research_85,85,"Anthony Potter, Boris Motik, Yavor Nenov and Ian Horrocks",Potter,Distributed RDF Query Answering with Dynamic Data Exchange,research,Querying/SPARQL (II),1,Anthony Potter,research_85.pdf,502,2016-10-21T13:30:00,2016-10-21T13:50:00,"Evaluating joins over RDF data stored in a shared-nothing server cluster is key
  to processing truly large RDF datasets. To the best of our knowledge, the
  existing approaches use a variant of the data exchange operator that is
  inserted into the query plan statically (i.e., at query compile time) to
  shuffle data between servers. We argue that this often misses opportunities for
  local computation, and we present a novel solution to distributed query
  answering that consists of two main components. First, we present a query
  answering algorithm based on dynamic data exchange, which exploits data
  locality better than the static approaches. Second, we present a partitioning
  algorithm for RDF data based on graph partitioning whose aim is to increase
  data locality. We have implemented our approach in the RDFox system, and our
  performance evaluation suggests that our techniques outperform the state of the
  art by up to an order of magnitude."
  research_149,149,"Armen Inants, Manuel Atencia and Jérôme Euzenat",Inants,Algebraic calculi for weighted ontology alignments,research,Ontology Matching,1,Armen Inants,research_149.pdf,502,2016-10-20T10:30:00,2016-10-20T10:50:00,"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."
  demo_20,20,"Eugene Siow, Thanassis Tiropanis and Wendy Hall",Siow,PIOTRe: Personal Internet of Things Repository,demo,Poster and Demo session,34,Eugene Siow,demo_20.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Resource-constrained Internet of Things (IoT) devices like Raspberry Pis', with specific performance optimisation, can serve as interoperable personal Linked Data repositories for IoT applications. In this demo paper we describe PIOTRe, a personal datastore that utilises our sparql2sql query translation technology on Pis' to process, store and publish IoT time-series historical data and streams. We demonstrate, for a smart home scenario with PIOTRe: a real-time dashboard that utilises RDF stream processing, a set of descriptive analytics visualisations on historical data, a framework for registering stream queries within a local network and a means of sharing metadata globally with HyperCat and Web Observatories."
  demo_27,27,"Francesco Osborne, Angelo Antonio Salatino, Aliaksandr Birukou and Enrico Motta",Osborne,Smart Topic Miner: Supporting Springer Nature Editors with Semantic Web Technologies,demo,Poster and Demo session,35,Francesco Osborne,demo_27.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Academic publishers, such as Springer Nature, annotate scholarly products with the appropriate research topics and keywords to facilitate the marketing process and to support (digital) libraries and academic search engines. This critical process is usually handled manually by experienced editors, leading to high costs and slow throughput. In this demo paper, we present Smart Topic Miner (STM), a semantic application designed to support the Springer Nature Computer Science editorial team in classifying scholarly publications. STM analyses conference proceedings and annotates them with a set of topics drawn from a large automatically generated ontology of research areas and a set of tags from Springer Nature Classification. "
  demo_26,26,"Fabian M. Suchanek, Colette Menard, Meghyn Bienvenu and Cyril Chapellier",Suchanek,What if machines could be creative?,demo,Poster and Demo session,36,Fabian M. Suchanek,demo_26.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this demo proposal, we present a system that proposes generations of existing concepts such as ""cars that park automatically""or ""skyscrapers made of glass""."
  doctoralconsortium_8,8,Valentina Ivanova,Ivanova,Applications of Large Displays: Advancing User Support in Large Scale Ontology Alignment,doctoralconsortium,Session 3,2,Valentina Ivanova,doctoralconsortium_8.pdf,,2016-10-18T16:15:00,2016-10-18T16:30:00,"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_9,9,Muhammad Amith,Amith,Ontology-based dialogue systems for improved patient HPV vaccine knowledge and perception,doctoralconsortium,Session 1,2,Muhammad Amith,doctoralconsortium_9.pdf,,2016-10-18T11:15:00,2016-10-18T11:30:00,"In Sir Tim Berners-Lee’s seminal article that introduce his vision of the semantic web, one of the use-cases described was a health- related example where health consumers utilized intelligent hand-held devices that aggregated and exchanged health data from the semantic web. Presently, majority of health consumers and patients rely on personal technology and the web to find information and to make personal health decisions. This proposal aims to contribute towards that use-case, specifically in the “hot-bed” issue of human papillomavirus (HPV) vac- cine. The HPV vaccine targets young adults and teens to protect against life-threatening cancers, yet a segment of the public has reservations against the vaccine. I propose an interactive dialogue agent that harness patient-level vaccine information encoded in an ontology that can be “talked to” with a natural language interface using utterances. I aim to pilot this technology in a clinic to assess if patient knowledge about HPV and the vaccine is increased, and if their attitude toward the vaccine is modified as a result of using the interactive agent."
  doctoralconsortium_4,4,Kleanthi Georgala,Georgala,Scalable Link Discovery for Modern Data-Driven Applications,doctoralconsortium,Session 2,5,Kleanthi Georgala,doctoralconsortium_4.pdf,,2016-10-18T15:00:00,2016-10-18T15:15:00,"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."
  research_304,304,"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,research_304.pdf,504+505,2016-10-19T14:00:00,2016-10-19T14:20:00,"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."
  doctoralconsortium_2,2,Le Tuan Anh,Anh,Linked Data processing for Embedded Devices,doctoralconsortium,Session 1,4,Le Tuan Anh,doctoralconsortium_2.pdf,,2016-10-18T11:45:00,2016-10-18T12:00:00,"Our PhD work aims to a comprehensive, scalable and resourced-awareness
  software framework to process RDF data for embedded devices.
  In this proposal, we introduce a system architecture supporting RDF storage,
  SPARQL query, RDF reasoning and continuous query for RDF stream. The ar-
  