Abstract
A parallel and scalable On-Line Analytical processing (OLAP) and data mining framework for large data sets is presented. The PARSIMONY platform which is used both for OLAP and data mining is described. Sparsity of data sets is handled by using sparse chunks using a bit-encoded sparse structure for compression, which enables aggregate operations on compressed data. Techniques for effectively using summary information available in data cubes for data mining are presented for mining Association rules and decision-tree based Classification.
| Original language | English (US) |
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| Pages | 178-186 |
| Number of pages | 9 |
| State | Published - 1999 |
| Event | Proceedings of the 1999 International Database Engineering and Application Symposium, IDEAS'99 - Montreal, Que, Can Duration: Aug 2 1999 → Aug 4 1999 |
Conference
| Conference | Proceedings of the 1999 International Database Engineering and Application Symposium, IDEAS'99 |
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| City | Montreal, Que, Can |
| Period | 8/2/99 → 8/4/99 |
ASJC Scopus subject areas
- General Computer Science
- General Engineering