Difference between revisions of "Mining Domain-Specific Thesauri from Wikipedia: a Case Study"

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'''Mining Domain-Specific Thesauri from Wikipedia: a Case Study''' - scientific work related to Wikipedia quality published in 2006, written by David N. Milne, Olena Medelyan and Ian H. Witten.
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'''Mining Domain-Specific Thesauri from Wikipedia: a Case Study''' - scientific work related to [[Wikipedia quality]] published in 2006, written by [[David N. Milne]], [[Olena Medelyan]] and [[Ian H. Witten]].
  
 
== Overview ==
 
== Overview ==
Domain-specific thesauri are high-cost, high-maintenance, high-value knowledge structures. Authors show how the classic thesaurus structure of terms and links can be mined automatically from Wikipedia. In a comparison with a professional thesaurus for agriculture authors find that Wikipedia contains a substantial proportion of its concepts and semantic relations; furthermore it has impressive coverage of contemporary documents in the domain. Thesauri derived using techniques capitalize on existing public efforts and tend to reflect contemporary language usage better than their costly, painstakingly-constructed manual counterparts.
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Domain-specific thesauri are high-cost, high-maintenance, high-value knowledge structures. Authors show how the classic thesaurus structure of terms and links can be mined automatically from [[Wikipedia]]. In a comparison with a professional thesaurus for agriculture authors find that Wikipedia contains a substantial proportion of its concepts and semantic relations; furthermore it has impressive coverage of contemporary documents in the domain. Thesauri derived using techniques capitalize on existing public efforts and tend to reflect contemporary language usage better than their costly, painstakingly-constructed manual counterparts.

Revision as of 08:16, 2 May 2020

Mining Domain-Specific Thesauri from Wikipedia: a Case Study - scientific work related to Wikipedia quality published in 2006, written by David N. Milne, Olena Medelyan and Ian H. Witten.

Overview

Domain-specific thesauri are high-cost, high-maintenance, high-value knowledge structures. Authors show how the classic thesaurus structure of terms and links can be mined automatically from Wikipedia. In a comparison with a professional thesaurus for agriculture authors find that Wikipedia contains a substantial proportion of its concepts and semantic relations; furthermore it has impressive coverage of contemporary documents in the domain. Thesauri derived using techniques capitalize on existing public efforts and tend to reflect contemporary language usage better than their costly, painstakingly-constructed manual counterparts.