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Clustering semantic relations for constructing and maintaining knowledge organization tools

Ibekwe-SanJuan, Fidelia (2006) Clustering semantic relations for constructing and maintaining knowledge organization tools. Journal of Documentation 62(2):pp. 229-250.

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Abstract

We propose a comprehensive methodology for thesaurus construction and maintenance combining shallow NLP with a clustering algorithm and an information visualization interface. The resulting system TermWatch, extracts terms from a text collection, mines semantic relations between them using complementary linguistic approaches and clusters terms using these semantic relations. The clusters formed exhibit the different relations necessary to populate a thesaurus or an ontology: synonymy, generic/specific and relatedness. The clusters represent, for a given term, its closest neighbours in terms of semantic relations. The clusters are mapped onto a 2D using an integrated visualization tool.
This could change the way in which information professionals (librarians and documentalists) undertake knowledge organization tasks. TermWatch can be useful either as a starting point for grasping the conceptual organization of knowledge in a huge text collection without having to read the texts, then actually serving as a suggestive tool for populating different hierarchies of a thesaurus or an ontology because its clusters are based on semantic relations.

Keywords:Knowledge organization, Thesaurus construction, Shallow NLP, Semantic relations acquisition, Term clustering, Information visualization.
Subjects:I. Information treatment for information services > IC. Index languages, processes and schemes.
I. Information treatment for information services > ID. Knowledge representation.
ID Code:12782
Deposited By:Ibekwe-SanJuan, Fidelia
Deposited On:26 February 2008
Alternative Locations:http://fidelia1.free.fr/
All fields:Show all fields

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