Incremental Rules Mining Algorithm Based on Incomplete Decision Table

The traditional approach to deal with incomplete information system is to make it completed, when a new object added only need a static attribute reduction algorithm to obtain the rules, wastes a lot of resources. The goal of incremental rules mining is to maintain the consistency of the rules in in...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 333-335; pp. 1314 - 1318
Main Authors Lu, Hong Yan, Yuan, Hong Chun, Wang, De Xing
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.01.2013
Subjects
Incomplete Decision Table
Discernable Matrix
Resolution Function
Incremental Rule Mining
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Summary:The traditional approach to deal with incomplete information system is to make it completed, when a new object added only need a static attribute reduction algorithm to obtain the rules, wastes a lot of resources. The goal of incremental rules mining is to maintain the consistency of the rules in incomplete decision table. When a new object is added, establish discernibility matrix of the original decision table, get distribution reduction set, then generate conjunctive items export rules set. It introduces incremental learning concept, avoids tedious counting process. It can be effective for large-scale incomplete ocean data reduction and it also provides a strong basis for decision making for the marine environment processing and follow-up processing.
Bibliography:Selected, peer reviewed papers from the 2013 2nd International Conference on Measurement, Instrumentation and Automation (ICMIA 2013), April 23-24, 2013, Guilin, China
ISBN:3037857501
9783037857502
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.333-335.1314