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: 2013
Pages: 17
Source title: Data Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-2455-9.ch086

Keywords: Data Mining / Data Mining and Databases / Information 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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