Extraits

Data mining is already incorporated into the business processes in many sectors such as health, retail, automotive, finance, telecom and insurance as well as in government. This technology is well established in applications such as targeted marketing, customer churn detection and market basket analysis. It is also emerging as an important technology in a wide range of new application areas, such as social media, social networks and sensor networks. These areas pose new challenges both in terms of the nature of available data and the underlying support technology. This book contains extended versions of a selection of papers presented at a series of workshops held between 2005 and 2008 on the subject of data mining for business applications. It covers the entire spectrum of issues involved in the development of data mining systems. Areas covered include methodological issues and research challenges, typical problems for which data mining has proved to be an invaluable tool, and innovative applications of data mining which make this an exciting field to work in. The contributions illustrate the importance of maintaining close contact between researchers and practitioners: it is essential that researchers are exposed to and motivated by the real problems and practical constraints experienced by organizations, and practitioners need to interact with the research community to identify new opportunities to apply the latest technology. This book will be of interest not only to data mining researchers and practitioners, but also to students seeking a better understanding of the practical issues involved in building data mining systems. Excerpted from Data Mining for Business Applications All rights reserved by the original copyright owners. Excerpts are provided for display purposes only and may not be reproduced, reprinted or distributed without the written permission of the publisher.