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Proceedings Paper

Context-sensitive keyword selection using text data mining
Author(s): Sai-Ming Li; Sanjeev Seereeram; Raman K. Mehra; Chris Miles
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Paper Abstract

Most information retrieval systems rely on the user to provide a set of keywords that the retrieved documents should contain. However, when the objective is to search for documents that is similar to a given document, the system has to choose the keywords from that document first. Automatic selection of keywords is not a trivial task as one word may be a keyword in one context but a very common word in others, and require significant domain specific knowledge. In this paper we describe a method for choosing keywords from a document within a given corpus automatically using text data-mining technique. The key idea is to score the words within the document based on the clustering result of the entire corpus. We applied the scheme to a Software Trouble Report (STR) corpus and obtained highly relevant keywords and search result.

Paper Details

Date Published: 12 March 2002
PDF: 10 pages
Proc. SPIE 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, (12 March 2002); doi: 10.1117/12.460238
Show Author Affiliations
Sai-Ming Li, Scientific Systems Co., Inc. (United States)
Sanjeev Seereeram, Scientific Systems Co., Inc. (United States)
Raman K. Mehra, Scientific Systems Co., Inc. (United States)
Chris Miles, U.S. Army Tank-Automotive and Armaments Command (United States)

Published in SPIE Proceedings Vol. 4730:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV
Belur V. Dasarathy, Editor(s)

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