Abstract
Rough sets for knowledge update have been successfully applied in data mining. Methods for incremental updating decision rules based on the indiscernibility, tolerance relation and similarity relations in rough set theory have been previously studied in literature. The characteristic relation-based rough sets approach provides more informative results than the approach employing the indiscernibility, tolerance relations and similarity relations based approach. In this paper, we extend rough sets based on characteristic relations for incrementally updating decision rules. An extensive experimental evaluation validates the efficiency of the proposed approach which may be used to handle a dynamic maintenance of decision rules in data mining.
Original language | English |
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Title of host publication | 2007 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2007 |
Publisher | IEEE Computer Society and the Association for Computing Machinery |
Pages | 3713-3716 |
Number of pages | 4 |
ISBN (Print) | 1424413125, 1424413125, 9781424413126, 9781424413126 |
DOIs | |
State | Published - 2007 |
Event | 2007 - WiCOM: International Conference on Wireless Communications, Networking and Mobile Computing - Shanghai Duration: 21 Sep 2007 → 25 Sep 2007 https://ieeexplore.ieee.org/xpl/conhome/4339774/proceeding |
Publication series
Name | 2007 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2007 |
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Conference
Conference | 2007 - WiCOM |
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Country/Territory | China |
City | Shanghai |
Period | 2007-09-21 → 2007-09-25 |
Internet address |
ASJC Scopus subject areas
- Computer Science Applications
- Electrical and Electronic Engineering
- Communication