Clustering semantic relations for constructing and maintaining knowledge organization tools

Ibekwe-SanJuan, Fidelia Clustering semantic relations for constructing and maintaining knowledge organization tools. Journal of Documentation, 2006, vol. 62, n. 2, pp. 229-250. [Journal article (Paginated)]

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English 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.

Item type: Journal article (Paginated)
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.
Depositing user: Fidelia Ibekwe-SanJuan
Date deposited: 26 Feb 2008
Last modified: 02 Oct 2014 12:10
URI: http://hdl.handle.net/10760/11147

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