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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. In: Natural language processing and information systems : 14th International Conference on Applications of Natural Language to Information Systems, NLDB 2009, Saarbrücken, Germany, June 24-26, 2009. Revised Papers. Lecture Notes in Computer Science . Springer, Berlin, pp. 301-302. ISBN 9783642125492

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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: Contribution in Book/Report/Proceedings
Uncontrolled Keywords: Information Retrieval ; Full Text Search ; Term extraction ; Termine ; Document clustering ; Natural Language processing
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?: No
Published?: Published
Last Modified: 22 May 2018 06:24
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