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Proceedings Paper

Project X: competitive intelligence data mining and analysis
Author(s): John F. Gilmore; Michael A. Pagels; Justin Palk
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Paper Abstract

Competitive Intelligence (CI) is a systematic and ethical program for gathering and analyzing information about your competitors' activities and general business trends to further your own company's goals. CI allows companies to gather extensive information on their competitors and to analyze what the competition is doing in order to maintain or gain a competitive edge. In commercial business this potentially translates into millions of dollars in annual savings or losses. The Internet provides an overwhelming portal of information for CI analysis. The problem is how a company can automate the translation of voluminous information into valuable and actionable knowledge. This paper describes Project X, an agent-based data mining system specifically developed for extracting and analyzing competitive information from the Internet. Project X gathers CI information from a variety of sources including online newspapers, corporate websites, industry sector reporting sites, speech archiving sites, video news casts, stock news sites, weather sites, and rumor sites. It uses individual industry specific (e.g., pharmaceutical, financial, aerospace, etc.) commercial sector ontologies to form the knowledge filtering and discovery structures/content required to filter and identify valuable competitive knowledge. Project X is described in detail and an example competitive intelligence case is shown demonstrating the system's performance and utility for business intelligence.

Paper Details

Date Published: 27 March 2001
PDF: 9 pages
Proc. SPIE 4384, Data Mining and Knowledge Discovery: Theory, Tools, and Technology III, (27 March 2001); doi: 10.1117/12.421081
Show Author Affiliations
John F. Gilmore, Veridian Systems, Inc. (United States)
Michael A. Pagels, Veridian Systems, Inc. (United States)
Justin Palk, Veridian Systems, Inc. (United States)


Published in SPIE Proceedings Vol. 4384:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology III
Belur V. Dasarathy, Editor(s)

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