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WEBKDD 2001 - Mining Web Log Data Across All Customers Touch Points

Third International Workshop, San Francisco, CA, USA, August 26, 2001, Revised Papers

  • Conference proceedings
  • © 2002

Overview

Editors:
  1. Ron Kohavi

    1. Blue Martini Software, San Mateo, USA

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  2. Brij M. Masand

    1. Data Miners Inc., Boston, USA

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  3. Myra Spiliopoulou

    1. Leipzig Graduate School of Management, Leipzig, Germany

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  4. Jaideep Srivastava

    1. University of Minnesota, Minneapolis

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2356)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: WebKDD 2001.

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Table of contents (7 papers)

  1. Front Matter

    Pages I-XI
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  2. Detail and Context in Web Usage Mining: Coarsening and Visualizing Sequences

    • Bettina Berendt
    Pages 1-24

  3. A Customer Purchase Incidence Model Applied to Recommender Services

    • Andreas Geyer-Schulz, Michael Hahsler, Maximillian Jahn
    Pages 25-47

  4. A Cube Model and Cluster Analysis for Web Access Sessions

    • Joshua Zhexue Huang, Michael Ng, Wai-Ki Ching, Joe Ng, David Cheung
    Pages 48-67

  5. Exploiting Web Log Mining for Web Cache Enhancement

    • Alexandros Nanopoulos, Dimitrios Katsaros, Yannis Manolopoulos
    Pages 68-87

  6. LOGML: Log Markup Language for Web Usage Mining

    • John R. Punin, Mukkai S. Krishnamoorthy, Mohammed J. Zaki
    Pages 88-112

  7. A Framework for Efficient and Anonymous Web Usage Mining Based on Client-Side Tracking

    • Cyrus Shahabi, Farnoush Banaei-Kashani
    Pages 113-144

  8. Mining Indirect Associations in Web Data

    • Pang-Ning Tan, Vipin Kumar
    Pages 145-166

  9. Back Matter

    Pages 167-167
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  1. WEBKDD 2001 — Mining Web Log Data Across All Customers Touch Points

Keywords

About this book

WorkshopTheme The ease and speed with which business transactions can be carried out over the Web has been a key driving force in the rapid growth of electronic commerce. In addition, customer interactions, including personalized content, e-mail c- paigns, and online feedback provide new channels of communication that were not previously available or were very ine?cient. The Web presents a key driving force in the rapid growth of electronic c- merceandanewchannelforcontentproviders.Knowledgeaboutthecustomeris fundamental for the establishment of viable e-commerce solutions. Rich web logs provide companies with data about their customers and prospective customers, allowing micro-segmentation and personalized interactions. Customer acqui- tion costs in the hundreds of dollars per customer are common, justifying heavy emphasis on correct targeting. Once customers are acquired, customer retention becomes the target. Retention through customer satisfaction and loyalty can be greatly improved by acquiring and exploiting knowledge about these customers and their needs. Althoughweblogsarethesourceforvaluableknowledgepatterns,oneshould keep in mind that the Web is only one of the interaction channels between a company and its customers. Data obtained from conventional channels provide invaluable knowledge on existing market segments, while mobile communication adds further customer groups. In response, companies are beginning to integrate multiple sources of data including web, wireless, call centers, and brick-a- mortar store data into a single data warehouse that provides a multifaceted view of their customers, their preferences, interests, and expectations.

Editors and Affiliations

  • Blue Martini Software, San Mateo, USA

    Ron Kohavi

  • Data Miners Inc., Boston, USA

    Brij M. Masand

  • Leipzig Graduate School of Management, Leipzig, Germany

    Myra Spiliopoulou

  • University of Minnesota, Minneapolis

    Jaideep Srivastava

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