Ali Harb

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The growing popularity of Web 2.0 provides with increasing numbers of documents expressing opinions on different topics. Recently, new research approaches have been defined in order to automatically extract such opinions from the Internet. They usually consider opinions to be expressed through adjectives, and make extensive use of either general(More)
In a context of decision-aid to support the identification of collaborative networks, this paper focuses on extracting essential facets of firm competencies. We present an approach for enrichment of competence ontology, based on two steps where a novel effective filtering step is utilized. First we extract the correlation between terms of a learning dataset(More)
Responding correctly to a question given a large collection of textual data is not an easy task. There is a need to perceive and recognize the question at a level that permits to detect some constraints that the question imposes on possible answers. The question classification task is used in Question Answering systems. This deduces the type of the expected(More)
RÉSUMÉ. La plupart des systèmes question/réponse se basent sur trois axes principaux : classification et analyse de la question, recherche de document pertinents et extraction de la réponse. La performance à chaque étape affecte le résultat final. La classification de question apparaît comme une tâche importante car elle infère le type de réponse attendu.(More)
Expressed opinions grows more and more on the Internet. Recently, extracting automatically such opinions becomes a topic addressed by new research work. Traditionally, detection of opinions is based on extracting adjectives. Existing methods are often based on general dictionaries. Unfortunately, main drawbacks of these approaches are that, for different(More)
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