This book constitutes the thoroughly refereed post-proceedings of the 8th International Workshop on Mining Web Data, WEBKDD 2006, held in Philadelphia, PA, USA in August 2006 in conjunction with the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2006.

The 13 revised full papers presented together with a detailed preface went through two rounds of reviewing and improvement and were carefully selected for inclusion in the book. The enhanced papers show new technologies from areas like adaptive mining methods, stream mining algorithms, techniques for the Grid, especially flat texts, documents, pictures and streams, usability, e-commerce applications, personalization, and recommendation engines.

This book constitutes the thoroughly refereed post-proceedings of the 6th International Workshop on Mining Web Data, WEBKDD 2004, held in Seattle, WA, USA in August 2004 in conjunction with the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2004.

The 11 revised full papers presented together with a detailed preface went through two rounds of reviewing and improvement and were carfully selected for inclusion in the book. The extended papers are subdivided into 4 general groups: Web usage analysis and user modeling, Web personalization and recommender systems, search personalization, and semantic Web mining. The latter contains also papers from the joint KDD workshop on Mining for and from the Semantic Web, MSW 2004.

This book constitutes the thoroughly refereed post-proceedings of the 7th International Workshop on Mining Web Data, WEBKDD 2005, held in Chicago, IL, USA in August 2005 in conjunction with the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2005. The nine revised full papers presented together with a detailed preface went through two rounds of reviewing and improvement and were carefully selected for inclusion in the book.

1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that - dress the unique challenges of discovering insights from Web usage data, aiming toevaluateWebusability, understandtheinterestsandexpectationsofusersand assess the e?ectiveness of content delivery. The maturing and expanding Web presents a key driving force in the rapid growth of electronic commerce and a new channel for content providers. Customized o?ers and content, made possible by discovered knowledge about the customer, are fundamental for the establi- ment of viable e-commerce solutions and sustained and e?ective content delivery in noncommercial domains. Rich Web logs provide companies with data about their online visitors and prospective customers, allowing microsegmentation and personalized interactions. While Web mining as a domain is several years old, the challenges that characterize data analysis in this area continue to be formidable. Though p- processing data routinely takes up a major part of the e?ort in data mining, Web usage data presents further challenges based on the di?culties of assigning data streams to unique users and tracking them over time. New innovations are required to reliably reconstruct sessions, to ascertain similarity and di?erences between sessions, and to be able to segment online users into relevant groups

After the advent of data mining and its successful application on conventional data, Web-related information has been an appropriate and increasingly popular target of knowledge discovery. Depending on whether the data used in the knowledge discovery process concerns the Web itself in terms of content or the usage of the content, one distinguishes between Web content mining and Web usage mining.This book is the first one entirely devoted to Web usage mining. It originates from the WEBKDD'99 Workshop held during the 1999 KDD Conference. The ten revised full papers presented together with an introductory survey by the volume editors documents the state of the art in this exciting new area. The book presents topical sections on Modeling the User, Discovering Rules and Patterns of Navigation, and Measuring interestingness in Web Usage Mining.