MeetingsFrom: Carsten Pohle Date: 12 Jul 2001 20:11:56 +0200 Subject: WebKDD-2001, Mining Log Data Across All Customer TouchPoints, Aug 26 WEBKDD 2001 Mining Log Data Across All Customer TouchPoints August 26, 2001, San Francisco, CA ================================================= 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/ ================================================= 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: ---------------------------- 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: -------------------------------- 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. |
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