Conference proceeding
An incremental algorithm for mining default definite decision rules from incomplete decision tables
GRC: 2007 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, PROCEEDINGS, pp 175-175
01 Jan 2007
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Abstract
The present paper puts forward an incremental algorithm for extracting default definite rules proposed by us from incomplete decision table using semi-equivalence classes derived from a semi-equivalence relation and their meet and join blocks on the universe. After default definite decision rules and constraint rules are acquired from the incomplete decision table, the incremental algorithm is used to mode them when new data is added to the incomplete information table. It does not need to process the original dataset repeatedly but only updates related data and rules. So it is effective in performing mining tasks from incomplete decision table. Through an example, a procedure for mining and revising rules is illustrated.
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Details
- Title
- An incremental algorithm for mining default definite decision rules from incomplete decision tables
- Creators
- Chen Wu - Jiangsu UniversityXiaohua Hu - Drexel University, Information ScienceXiajiong Shen - Henan Univ, Coll Comp & Informat Engn, Kailua, HI USAXiaodan Zhang - Drexel Univ, Coll & Informat Sci Technol, Philadelphia, PA 19104 USAYi Pan - Georgia State Univ, Dept Comp Sci, Atlanta, GA 30302 USA
- Publication Details
- GRC: 2007 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, PROCEEDINGS, pp 175-175
- Publisher
- IEEE
- Number of pages
- 2
- Grant note
- 240205; 240196 / PA Dept of Health Tobacco Settlement Formula 239667 / PA Dept of Health CCF 0514679 / NSF; National Science Foundation (NSF) IIS 0448023 / NSF Career; National Science Foundation (NSF); NSF - Office of the Director (OD)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000252984500037
- Other Identifier
- 991019167675704721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Hardware & Architecture
- Computer Science, Software Engineering
- Computer Science, Theory & Methods
- Engineering, Electrical & Electronic