A symbolic approach to automatic multiword term structuring

This paper presents a three-level structuring of multiword terms (MWTs) 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 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.