Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10369500 | Computer Speech & Language | 2005 | 19 Pages |
Abstract
This paper presents a three-level structuring of multiword terms basing on lexical inclusion, WordNet similarity and a clustering approach. Term clustering by automatic data analysis methods offers an interesting way of organizing a domain's knowledge structure, 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.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Eric SanJuan, James Dowdall, Fidelia Ibekwe-SanJuan, Fabio Rinaldi,