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The Role of Data Mining for Business Intelligence in Knowledge Management

The Role of Data Mining for Business Intelligence in Knowledge Management
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Author(s): Kijpokin Kasemsap (Suan Sunandha Rajabhat University, Thailand)
Copyright: 2015
Pages: 22
Source title: Integration of Data Mining in Business Intelligence Systems
Source Author(s)/Editor(s): Ana Azevedo (Algoritmi R&D Center/University of Minho, Portugal & Polytechnic Institute of Porto/ISCAP, Portugal)and Manuel Filipe Santos (Algoritmi R&D Center/University of Minho, Portugal)
DOI: 10.4018/978-1-4666-6477-7.ch002

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Abstract

This chapter introduces the role of Data Mining (DM) for Business Intelligence (BI) in Knowledge Management (KM), thus explaining the concept of KM, BI, and DM; the relationships among KM, BI, and DM; the practical applications of KM, BI, and DM; and the emerging trends toward practical results in KM, BI, and DM. In order to solve existing BI problems, this chapter also describes practical applications of KM, BI, and DM (in the fields of marketing, business, manufacturing, and human resources) and the emerging trends in KM, BI, and DM (in terms of larger databases, high dimensionality, over-fitting, evaluation of statistical significance, change of data and knowledge, missing data, relationships among DM fields, understandability of patterns, integration of other DM systems, and users' knowledge and interaction). Applying DM for BI in the KM environments will enhance organizational performance and achieve business goals in the digital age.

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