Search Results: 1 - 10 of 12 matches for " Biancamaria Gliozzo "
Abstract: This article presents the combination of Latent Semantic Analysis (LSA) with other natural language processing techniques (stemming, removal of closed-class words and word sense disambiguation) to improve the automatic assessment of students' free-text answers. The combinational schema has been tested in the experimental framework provided by the free-text Computer Assisted Assessment (CAA) system called Atenea (Alfonseca & Pérez, 2004). This system is able to ask randomly or according to the students' profile an open-ended question to the student and then, assign a score to it. The results prove that for all datasets, when the NLP techniques are combined with LSA, the Pearson correlation between the scores given by Atenea and the scores given by the teachers for the same dataset of questions improves. We believe that this is due to the complementarity between LSA, which works more at a shallow semantic level, and the rest of the NLP techniques used in Atenea, which are more focused on the lexical and syntactical levels. Este artículo presenta la combinación de Análisis Semántico Latente (LSA) con otras técnicas de procesamiento del lenguaje natural (lematización, eliminación de palabras funcionales y desambiguación de sentidos) para mejorar la evaluación automática de respuestas en texto libre. El sistema de evaluación de respuestas en texto libre llamado Atenea (Alfonseca & Pérez, 2004) ha servido de marco experimental para probar el esquema combinacional. Atenea es un sistema capaz de realizar preguntas, escogidas aleatoriamente o bien conforme al perfil del estudiante, y asignarles una calificación numérica. Los resultados de los experimentos demuestran que para todos los conjuntos de datos en los que las técnicas de PLN se han combinado con LSA la correlación de Pearson entre las notas dadas por Atenea y las notas dadas por los profesores para el mismo conjunto de preguntas mejora. La causa puede encontrarse en la complementariedad entre LSA, que trabaja a un nivel semántico superficial, y el resto de las técnicas NLP usadas en Atenea, que están más centradas en los niveles léxico y sintáctico.
Abstract: background and objectives: anxiety and depressive disorders represent an important public health problem, which involves not only the mental health services, but the general practice as well. this paper examines models of collaboration between general practice and community mental health services developed in italy. methods: different consultation -liaison activities are presented. for every collaboration model advantages and disadvantage are discussed. results: the structured consultation liaison service is based on supplying diagnostic consultation and therapeutic interventions in support of general practitioners (gps). the service could be based in either a community mental health centre (cmhc) or externally. diagnostic evaluation can be followed by brief and focal therapeutic interventions, in support of the gp's therapeutic plan. the spontaneous collaboration in small centres are frequent in rural areas where the contained dimensions of the services and the direct acquaintance between psychiatrists and gps encourage the personalization of the collaboration. the model of liaison and group-training focuses on direct contact between consultant and gps. in the course of regular meetings, the consultant gives the gps supervision and education, and they can discuss the therapeutic plans for patients requiring specialist intervention. conclusion: the empiric classification presented should be considered an attempt to represent a complex reality. every service, in fact, carries out activities that are necessarily wider than abstract typologies and that overlap with other models' activities.
Abstract: this article presents the combination of latent semantic analysis (lsa) with other natural language processing techniques (stemming, removal of closed-class words and word sense disambiguation) to improve the automatic assessment of students' free-text answers. the combinational schema has been tested in the experimental framework provided by the free-text computer assisted assessment (caa) system called atenea (alfonseca & pérez, 2004). this system is able to ask randomly or according to the students' profile an open-ended question to the student and then, assign a score to it. the results prove that for all datasets, when the nlp techniques are combined with lsa, the pearson correlation between the scores given by atenea and the scores given by the teachers for the same dataset of questions improves. we believe that this is due to the complementarity between lsa, which works more at a shallow semantic level, and the rest of the nlp techniques used in atenea, which are more focused on the lexical and syntactical levels.