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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | A symbolic approach to Automatic MultiWord Term Structuring |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Journal Title | Computer Speech and Language |
| Publisher | Elsevier Science |
| Geographical Reach | international |
| Date | 2004 |
| Abstract Text | 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 o?ers an inter- esting way of organizing a domainÕs 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. |
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