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Improving Full Text Search with Text Mining Tools

Piao, Scott and Rea, Brian and McNaught, John and Ananiadou, Sophia (2010) Improving Full Text Search with Text Mining Tools. Lecture Notes in Computer Science, 5723/2. pp. 301-302.

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Abstract

Today, academic researchers face a flood of information. Full text search provides an important way of finding useful information from mountains of publications, but it generally suffers from low precision, or low quality of document retrieval. A full text search algorithm typically examines every word in a given text, trying to find the query words. Unfortunately, many words in natural language are polysemous, and thus many documents retrieved using this approach are irrelevant to actual search queries.

Item Type: Article
Journal or Publication Title: Lecture Notes in Computer Science
Uncontrolled Keywords: Information Retrieval, Full Text Search, Term extraction, Termine, Document clustering, Natural Language processing
Subjects:
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 51589
Deposited By: ep_importer_pure
Deposited On: 25 Nov 2011 11:14
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 19:54
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/51589

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