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The continuous sophistication in clinical informationprocessing motivates the development of a dictionary likeWordNet for Medical Events in order to convey the valuableinformation (e.g., event definition, sense based contextualdescription, polarity etc.) to the experts (e.g. medicalpractitioners) and non-experts (e.g. patients) in their respective fields. The present paper reports the enrichment of...
This paper proposes a new text-based question answering system. It models knowledge in documents and questions with conceptual graph formalism (CGF). To prepare knowledge to be modeled, natural language processing is applied to the text using OpenNLP, and then syntactic and semantic information is realized using VerbNet and WordNet. We handle different types of questions, especially questions constructed...
Word Sense Disambiguation in text is still a difficult problem as the best supervised methods require laborious and costly manual preparation of training data. On the other hand, the unsupervised methods express significantly lower accuracy and produce results that are not satisfying for many application. The goal of this work is to develop a model of Word Sense Disambiguation which minimises the...
The focus of data integration systems is on producing a comprehensive global schema successfully integrating data from heterogeneous data sources (heterogeneous in format and in structure). Starting from the ldquomeaningsrdquo associated to schema elements (i.e. class/attribute labels) and exploiting the structural knowledge of sources, it is possible to discover relationships among the elements of...
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