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.
Full text not available from this repository.Official URL: http://dx.doi.org/10.1007/978-3-642-12550-8_29
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: | UNSPECIFIED |
| 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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