Web Usage Analysis and User Profiling

International WEBKDD'99 Workshop San Diego, CA, USA, August 15, 1999 Revised Papers
2000
ISBN: 978-3-540-67818-2
Verlag: Springer Berlin Heidelberg

Buch, Englisch, 182 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 306 g

Reihe: Lecture Notes in Artificial Intelligence

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.

Zielgruppe

Research

Autoren/Hrsg.

Spiliopoulou, Myra

Masand, Brij

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik Hardware: Grundlagen und Allgemeines
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Internet, E-Mail, VoIP
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Webprogrammierung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Sozialwissenschaften Medien- und Kommunikationswissenschaften Kommunikationswissenschaften Digitale Medien, Internet, Telekommunikation
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Digital Lifestyle Internet, E-Mail, Social Media

Inhaltsverzeichnis

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.