Advances in Data Mining

1. Front Matter

   Pages I-VI

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2. Data Mining and E-commerce

   1. Sequence Rules for Web Clickstream Analysis

      • Erika Blanc, Paolo Giudici

      Pages 1-14

   2. Data Mining of Association Rules and the Process of Knowledge Discovery in Databases

      • Jochen Hipp, Ulrich Güntzer, Gholamreza Nakhaeizadeh

      Pages 15-36

   3. Intelligent E-marketing with Web Mining, Personalization, and User-Adpated Interfaces

      • Petra Perner, G. Fiss

      Pages 37-52

3. Knowledge Management and Data Mining

   1. The indiGo Project: Enhancement of Experience Management and Process Learning with Moderated Discourses

      • Klaus-Dieter Althoff, Ulrike Becker-Kornstaedt, Björn Decker, Andreas Klotz, Edda Leopold, Jörg Rech et al.

      Pages 53-79

4. Medical Applications

   1. Genomic Data Explosion — The Challenge for Bioinformatics?

      • Änne Glass, Thomas Karopka

      Pages 80-98

   2. Case-Based Reasoning for Prognosis of Threatening Influenza Waves

      • Rainer Schmidt, Lothar Gierl

      Pages 99-107

5. Back Matter

   Pages 109-109

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This book presents papers describing selected projects on the topic of data mining in fields like e commerce, medicine, and knowledge management. The objective is to report on current results and at the same time to give a review on the present activities in this field in Germany. An effort has been made to include the latest scientific results, as well as lead the reader to the various fields of activity and the problems related to them. Knowledge discovery on the basis of web data is a wide and fast growing area. E commerce is the principal theme of motivation in this field, as companies invest large sums in the electronic market, in order to maximize their profits and minimize their risks. Other applications are telelearning, teleteaching, service support, and citizen information systems. Concerning these applications, there is a great need to understand and support the user by means of recommendation systems, adaptive information systems, as well as by personalization. In this respect Giudici and Blanc present in their paper procedures for the generation of associative models from the tracking behavior of the user. Perner and Fiss present in their paper a strategy for intelligent e marketing with web mining and personalization. Methods and procedures for the generation of associative rules are presented in the paper by Hipp, Güntzer, and Nakhaeidizadeh.

• E-Commerce
• data mining
• e-marketing
• knowledge discovery
• knowledge management
• learning
• marketing
• web mining

• Institute of Computer Vision and Applied Science, Leipzig, Germany

  Petra Perner

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