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Computer Science - Database Management & Information Retrieval | Data Mining - Special Issue in Annals of Information Systems

Data Mining

Special Issue in Annals of Information Systems

Stahlbock, Robert, Crone, Sven F., Lessmann, Stefan (Eds.)

2010, XIII, 387p.

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  • Provides a state-of-art, up-to-the moment, view of the evolving field of data mining
  • Special publication of the 2007 International Conference on Data Mining (DMIN 07)
  • Features a combination of rigorously peer-reviewed theoretical research papers, as well as industrial reports, and case studies on applications

Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research.

This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN’07 and DMIN’08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining.

Content Level » Research

Keywords » Business Intelligence - Text Mining - classification - data analysis - data mining - knowledge discovery - statistics

Related subjects » Business, Economics & Finance - Business & Management - Database Management & Information Retrieval - Operations Research & Decision Theory - Production & Process Engineering

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