Meetings

                             WEBKDD 2001
           Mining Log Data Across All Customer TouchPoints
                  August 26, 2001, San Francisco, CA
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http://robotics.Stanford.EDU/~ronnyk/WEBKDD2001/index.html
webkdd@cs.stanford.edu

In conjunction with the

      ACM-SIGKDD Conference on Knowledge Discovery in Databases
                               KDD'2001
http://www.acm.org/sigkdd/kdd2001/

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WEBKDD'01 is the third of a successful series of workshops. It aims
to bring together practitioners of web-commerce, wap-commerce, call
centers, and brick-and-mortar stores with tool vendors and data mining
researchers in order to foster the exchange of ideas and the dissemination
of emerging solutions related to customer interactions across multiple
touchpoints and to the customer retention and acquisition policies that
can be derived from the analysis of these interactions.


Instructions for attendance:
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To attend WEBKDD'01,
- You must register to KDD'01.
AND
- You must additionally fill the "request to attend" form at the
  WEBKDD'01 homepage, since attendance is by invitation only.

Accepted papers:
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Cyrus Shahabi, Jabed Faruque, Milad Ershaghi,
Farnoush Banaei-Kashani:
  A Reliable, Efficient, and Scalable System for
  Web Usage Data Acquisition

Andreas Geyer-Schulz, Michael Hahsler, Maximillian Jahn:
  A Customer Purchase Incidence Model Applied to
  Recommender Systems for Web Sites


Lars Schmidt-Thieme, Wolfgang Gaul
  Modeling Web User Navigational Behavior

John R. Punin, Mukkai S. Krishnamoorthy, Mohammed J. Zaki
  Languages and Algorithms for Web Usage Mining


Shigeru Oyanagi, Kazuto Kubota, Akihiko Nakase
  Application of Matrix Clustering to Web Log
  Analysis and Access Prediction


Joshua Zhexue Huang, Joe Ng, David W. Cheung, Michael K. Ng
  A Cube Model for Web Access Sessions and Cluster Analysis


Pang-Ning Tan, Vipin Kumar
  Mining Indirect Associations in Web Data


Bettina Berendt
  Understanding web usage at different levels of
  abstraction: coarsening and visualizing
  sequences

Alexandros Nanopoulos, Dimitrios Katsaros, Yannis Manolopoulos
  Effective Prediction of Web-user Accesses:
  A Data Mining Approach

The workshop papers will be published by Springer-Verlag in LNAI
(Lecture Notes in Artificial Intelligence) as a post-proceedings book.