Web Usage Analysis and User Profiling
International WEBKDD'99 Workshop San Diego, CA, USA, August 15, 1999 Revised Papers
Published on 26. July 2000
Book
Paperback/Softback
V, 182 pages
978-3-540-67818-2 (ISBN)
Description
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.
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.
More details
Series
Edition
2000 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
V, 182 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 11 mm
Weight
306 gr
ISBN-13
978-3-540-67818-2 (9783540678182)
DOI
10.1007/3-540-44934-5
Schweitzer Classification
Content
Modelling the Users.- Inferring Demographic Attributes of Anonymous Internet Users.- A Generalization-Based Approach to Clustering of Web Usage Sessions.- Constructing Web User Profiles: A Non-invasive Learning Approach.- Data Mining the Internet and Privacy.- Discovering Rules and Patterns of Navigation.- User-Driven Navigation Pattern Discovery from Internet Data.- Data Mining of User Navigation Patterns.- Making Web Servers Pushier.- Measuring Interestingness in Web Usage Mining.- Analysis and Visualization of Metrics for Online Merchandising.- Improving the Effectiveness of a Web Site with Web Usage Mining.- Discovery of Interesting Usage Patterns from Web Data.