Date: Fri, 18 Dec 1998 13:38:23 -0500 From: Foster Provost, foster@Basit.COM Subject: CFP: KDD-99 Web: http://research.microsoft.com/datamine/kdd99/Call for Papers KDD-99: The ACM SIGKDD Fifth International Conference on Knowledge Discovery and Data Mining August 15-18, 1999, San Diego, CA, USA http://research.microsoft.com/datamine/kdd99/ Sponsored by: Association for Computing Machinery (ACM) - SIGKDD Co-sponsored by: AAAI, ACM SIGMOD, and ACM SIGART The continuing rapid growth of on-line data and the widespread use of databases necessitate the development of techniques for extracting useful knowledge and for facilitating database access. The challenge of extracting knowledge from data is of common interest to several fields, including statistics, databases, pattern recognition, machine learning, data visualization, optimization, and high-performance computing. KDD-99 will focus on techniques, applications, and experiences, bringing together researchers and practitioners. Starting this year, the KDD series will represent the annual conferences of the newly formed SIGKDD--the ACM Special Interest Group on Knowledge Discovery and Data Mining. -------- Calendar -------- Electronic abstracts due: March 1, 1999 Submissions due: March 5, 1999 Notification of acceptance/rejection: May 17, 1999 Camera-ready copies due: June 14, 1999 Submission Guidelines: Please see the KDD-99 web site for detailed instructions (http://research.microsoft.com/datamine/KDD99). All submissions (including research papers, panels, demos, tutorials and industrial track submissions) must be received by March 5, 1998. Prospective authors are encouraged to submit research papers on any topics of relevance to knowledge discovery and data mining. In addition to fundamental research, we solicit papers fostering cross-fertilization and interdisciplinary integration, as well as papers that describe significant experiences and implementation lessons. Topics of interest include, but are not limited to: KDD Techniques Human Interaction and the KDD Process --- ---------- ----- ----------- --- --- --- ------- New KDD algorithms Data and knowledge visualization Mining the Web Evaluating knowledge and potential discoveries Text/multimedia Interactive exploration Data cleaning/noisy data Visualizing large, high-dimensional data Incremental algorithms High-dimensional data Background knowledge Mining Enterprise Databases ------ ---------- --------- Implementation and Applications Scalable algorithms -------------- --- ------------ Unification of mining with querying Implementation & use of KDD systems Database architectures for KDD Vertical applications Database primitives for KDD Case studies: success/failure Integration: mining/warehousing/OLAP Benchmarks KDD-99 Organization --- -- ------------ Program Committee Co-Chairs: Surajit Chaudhuri (SurajitC@microsoft.com) David Madigan (madigan@stat.washington.edu) General Chair: Usama Fayyad (Fayyad@microsoft.com) Awards: G. Piatetsky-Shapiro (gps@kstream.com) Demos/Exhibits: Ismail Parsa (iparsa@epsilon.com) Industrial/Applications Track: Jim Gray (gray@microsoft.com) Ronny Kohavi (ronnyk@bluemartini.com) Local Arrangements: Jenny Zhang (jgz@hnc.com) Panels: Padhraic Smyth (smyth@ics.uci.edu) Proceedings: Kyuseok Shim (shim@research.bell-labs.com) Publicity: Foster Provost (provost@acm.org) Sponsorship: Ramasamy Uthurusamy (samy@iss.gm.com) Tutorials: Jiawei Han (han@cs.sfu.ca) Workshops: Rakesh Agrawal (ragrawal@almaden.ibm.com)
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