A symbolic approach to automatic multiword term structuring.

Abstract : This paper presents a three-level structuring of multiword terms (MWTs) basing on lexical inclusion, WordNet similarity and a clustering approach. Term cluster- ing by automatic data analysis methods offers an interesting way of organizing a domain's knowledge structures, useful for several information-oriented tasks like science and technology watch, textmining, computer-assisted ontology population, Question Answering(Q-A). This paper explores how this three-level term structuring brings to light the knowledge structures from a corpus of genomics and compares the mapping of the domain topics against a hand-built ontology (the GENIA ontology). Ways of integrating the results into a Q-A system are discussed.
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Eric Sanjuan, James Dowdall, Fidelia Ibekwe-Sanjuan, Fabio Rinaldi. A symbolic approach to automatic multiword term structuring.. Computer Speech and Language, Elsevier, 2005, 19 (4), pp.524-542. ⟨10.1016/j.csl.2005.02.002⟩. ⟨hal-00636158⟩

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