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Chapitre D'ouvrage Année : 2011

Topic Extraction for Ontology Learning

Résumé

This chapter addresses the issue of topic extraction from text corpora for ontology learning. The first part provides an overview of some of the most significant solutions present today in the literature. These solutions deal mainly with the inferior layers of the Ontology Learning Layer Cake. They are related to the challenges of the Terms and Synonyms layers. The second part shows how the same pieces can be bound together into an integrated system for extracting meaningful topics. Whereas the extracted topics are not full concepts yet, they constitute a convincing approach in concept building and therefore in ontology learning. The chapter concludes by discussing the research done for filling the gap between topics and concepts as well as perspectives that emerge today in the topic learning area.
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Dates et versions

hal-00590557 , version 1 (03-05-2011)

Identifiants

Citer

Marian-Andrei Rizoiu, Julien Velcin. Topic Extraction for Ontology Learning. Wilson Wong, Wei Liu and Bennamoun, Mohammed. Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances, IGI Global, pp.38--61, 2011, ⟨10.4018/978-1-60960-625-1.ch003⟩. ⟨hal-00590557⟩
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