Supporting Data Mining of Large Databases by Visual Feedback Queries.

@inproceedings{DBLP:conf/icde/KeimKS94,
  author    = {Daniel A. Keim and
               Hans-Peter Kriegel and
               Thomas Seidl},
  title     = {Supporting Data Mining of Large Databases by Visual Feedback
               Queries},
  booktitle = {Proceedings of the Tenth International Conference on Data Engineering,
               February 14-18, 1994, Houston, Texas, USA},
  publisher = {IEEE Computer Society},
  year      = {1994},
  isbn      = {0-8186-5400-7},
  pages     = {302-313},
  ee        = {db/conf/icde/KeimKS94.html},
  crossref  = {DBLP:conf/icde/94},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

Copyright © 1994 by The Institute of Electrical and Electronic Engineers, Inc. (IEEE). Abstract used with permission.

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Referenced by

1. Edwin M. Knorr, Raymond T. Ng: Finding Aggregate Proximity Relationships and Commonalities in Spatial Data Mining. IEEE Trans. Knowl. Data Eng. 8(6): 884-897(1996)
2. Daniel A. Keim, Hans-Peter Kriegel: Visualization Techniques for Mining Large Databases: A Comparison. IEEE Trans. Knowl. Data Eng. 8(6): 923-938(1996)
3. Ming-Syan Chen, Jiawei Han, Philip S. Yu: Data Mining: An Overview from a Database Perspective. IEEE Trans. Knowl. Data Eng. 8(6): 866-883(1996)
4. Takeshi Fukuda, Yasuhiko Morimoto, Shinichi Morishita, Takeshi Tokuyama: Data Mining Using Two-Dimensional Optimized Accociation Rules: Scheme, Algorithms, and Visualization. SIGMOD Conference 1996: 13-23
5. Daniel A. Keim, Hans-Peter Kriegel: VisDB: A System for Visualizing Large Databases. SIGMOD Conference 1995: 482
6. Raymond T. Ng, Jiawei Han: Efficient and Effective Clustering Methods for Spatial Data Mining. VLDB 1994: 144-155