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WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles

4th International Workshop, Edmonton, Canada, July 23, 2002, Revised Papers

Editors: Zaiane, O.R., Srivastava, J., Spiliopoulou, M., Masand, B. (Eds.)

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About this 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.

Table of contents (10 chapters)

Table of contents (10 chapters)
  • LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition

    Chi, Ed H. (et al.)

    Pages 1-16

  • Mining eBay: Bidding Strategies and Shill Detection

    Shah, Harshit S. (et al.)

    Pages 17-34

  • Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models

    Ypma, Alexander (et al.)

    Pages 35-49

  • Web Usage Mining by Means of Multidimensional Sequence Alignment Methods

    Hay, Birgit (et al.)

    Pages 50-65

  • A Customizable Behavior Model for Temporal Prediction of Web User Sequences

    Frías-Martínez, Enrique (et al.)

    Pages 66-85

Buy this book

eBook $69.99
price for USA in USD (gross)
  • ISBN 978-3-540-39663-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $89.99
price for USA in USD
  • ISBN 978-3-540-20304-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles
Book Subtitle
4th International Workshop, Edmonton, Canada, July 23, 2002, Revised Papers
Editors
  • Osmar R. Zaiane
  • Jaideep Srivastava
  • Myra Spiliopoulou
  • Brij Masand
Series Title
Lecture Notes in Artificial Intelligence
Series Volume
2703
Copyright
2003
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-39663-5
DOI
10.1007/b11784
Softcover ISBN
978-3-540-20304-9
Edition Number
1
Number of Pages
IX, 183
Topics