Helping Online Customers Decide through Web Personalization
IEEE Intelligent Systems
Lessons and Challenges from Mining Retail E-Commerce Data
Machine Learning
Ethical issues in web data mining
Ethics and Information Technology
Digital Content Recommender on the Internet
IEEE Intelligent Systems
Applying knowledge engineering techniques to customer analysis in the service industry
Advanced Engineering Informatics
Mining the text information to optimizing the customer relationship management
Expert Systems with Applications: An International Journal
Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams
Proceedings of the 2010 conference on Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams
Expert Systems with Applications: An International Journal
Keeping track of customer life cycle to build customer relationship
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
A CBR system for injection mould design based on ontology: A case study
Computer-Aided Design
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From the Publisher:Web sites gather a lot of detailed information about customers. Unfortunately, most companies lack the know-how to capitalize on this information in order to improve their marketing and customer support functions. Considered by most experts to be the new frontier in the database and data warehousing fields, data mining can help change all this. Data mining techniques can be applied to the Web with results that can lead to more efficient and successful advertising campaigns, better customer service, and, ultimately, increased profits. Written by two bestselling data mining authors, Mining the Web shows you how to identify your most profitable customers, attract them, and, most importantly, keep them coming back. Linoff and Berry review specific data mining and analysis techniques for monitoring customer behavior and explain how to conduct marketing tests to better understand customers.