Overview

This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Mining Web Data, WEBKDD 2001 held in San Francisco, CA, USA in August 2001. The seven revised full papers went through two rounds of reviewing an improvement. The book addresses key issues in mining Web log data for e-commerce. The papers are devoted to predicting user access, recommender systems and access modeling, and acquiring and modeling data and patterns.

Full Product Details

Author:   Ron Kohavi ,  Brij M. Masand ,  Myra Spiliopoulou ,  Jaideep Srivastava
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2002 ed.
Volume:   2356
Dimensions:   Width: 15.50cm , Height: 0.90cm , Length: 23.50cm
Weight:   0.590kg
ISBN:  

9783540439691

ISBN 10:   3540439692
Pages:   166
Publication Date:   19 July 2002
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Detail and Context in Web Usage Mining: Coarsening and Visualizing Sequences.- A Customer Purchase Incidence Model Applied to Recommender Services.- A Cube Model and Cluster Analysis for Web Access Sessions.- Exploiting Web Log Mining for Web Cache Enhancement.- LOGML: Log Markup Language for Web Usage Mining.- A Framework for Efficient and Anonymous Web Usage Mining Based on Client-Side Tracking.- Mining Indirect Associations in Web Data.

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