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Workshop report: 2000 ACM SIGMOD workshop on research issues in data mining and knowledge discovery

Workshop report: 2000 ACM SIGMOD workshop on research issues in data mining and knowledge discovery Workshop Report: 2000 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery Dimitrios Gunopulos University of California Riverside, CA dg@cs.ucr.edu The 2000 Workshop on Research Issues in D a t a Mining and Knowledge Discovery (DMKD) was held on May 14, 2000 in Dallas in conjunction with the ACM SIGMOD 2000 conference. In the call for papers, in addition to novel d a t a mining algorithms and experiences in deploying d a t a mining systems and applications, we solicited papers on the following three important topics: ¢ F o u n d a t i o n s o f d a t a m i n i n g . There are numerous techniques t h a t fall under the broad umbrella of " d a t a mining" algorithms (e.g., association rules, classification, clustering). A framework or model t h a t unifies these disparate techniques would be a major contribution to the field (e.g., is d a t a mining simply the process of generating "good" summaries of the data?). ¢ D a t a m i n i n g t e c h n i q u http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGKDD Explorations Newsletter Association for Computing Machinery

Workshop report: 2000 ACM SIGMOD workshop on research issues in data mining and knowledge discovery

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2000 by ACM Inc.
ISSN
1931-0145
DOI
10.1145/360402.360431
Publisher site
See Article on Publisher Site

Abstract

Workshop Report: 2000 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery Dimitrios Gunopulos University of California Riverside, CA dg@cs.ucr.edu The 2000 Workshop on Research Issues in D a t a Mining and Knowledge Discovery (DMKD) was held on May 14, 2000 in Dallas in conjunction with the ACM SIGMOD 2000 conference. In the call for papers, in addition to novel d a t a mining algorithms and experiences in deploying d a t a mining systems and applications, we solicited papers on the following three important topics: ¢ F o u n d a t i o n s o f d a t a m i n i n g . There are numerous techniques t h a t fall under the broad umbrella of " d a t a mining" algorithms (e.g., association rules, classification, clustering). A framework or model t h a t unifies these disparate techniques would be a major contribution to the field (e.g., is d a t a mining simply the process of generating "good" summaries of the data?). ¢ D a t a m i n i n g t e c h n i q u

Journal

ACM SIGKDD Explorations Newsletter – Association for Computing Machinery

Published: Jun 1, 2000

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