Context-sensitive keyword selection using text data mining

Sai-Ming Li; Sanjeev Seereeram; Raman K. Mehra; Chris Miles

doi:10.1117/12.460238

12 March 2002 Context-sensitive keyword selection using text data mining

Sai-Ming Li, Sanjeev Seereeram, Raman K. Mehra, Chris Miles

Proceedings Volume 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV; (2002) https://doi.org/10.1117/12.460238
Event: AeroSense 2002, 2002, Orlando, FL, United States

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.

Citation Download Citation

Sai-Ming Li, Sanjeev Seereeram, Raman K. Mehra, and Chris Miles "Context-sensitive keyword selection using text data mining", Proc. SPIE 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, (12 March 2002); https://doi.org/10.1117/12.460238

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