Discovering Patterns in Order to Detect Weak Signals and Define New Strategies

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Author(s): Anass El Haddadi (University of Toulouse III, France & University of Mohamed V, Morocco), Bernard Dousset (University of Toulouse, France)and Ilham Berrada (University of Mohamed V, Morocco)
Copyright: 2012
Pages: 17
Source title: Pattern Discovery Using Sequence Data Mining: Applications and Studies
Source Author(s)/Editor(s): Pradeep Kumar (Indian Institute of Management, India), P. Radha Krishna (Infosys Technologies Limited, India)and S. Bapi Raju (University of Hyderabad, India)
DOI: 10.4018/978-1-61350-056-9.ch012

Keywords: Data Mining / Data Mining and Databases / Engineering Science Reference / Library & Information Science

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Abstract

Competitive intelligence activities rely on collecting and analyzing data in order to discover patterns from data using sequence data mining. The discovered patterns are used to help decision-makers considering innovation and defining the strategy for their business. In this chapter we present four methods for discovering patterns in the competitive intelligence process: “correspondence analysis,” “multiple correspondence analysis,” “evolutionary graph,” and “multi-term method.”

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