2011•Unpublished venueRequires access

The Decision Rules Mining Algorithm of Information System Based on Rough Set

Hongxin Wan, Yun Peng

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Abstract

There are many uncertainties of the data in information systems, which affects the extraction of decision rules. Using rough set to deal with these non-precise data can achieve effective decision-making rules by deleting redundant attributes. Through the relationship of key attributes, we can get association rules in a higher interested degree. The rules reflected the decision-making feature between attributes can provide decision support for policy-makers.This paper describes the implementation of rough set theory in incomplete data decision and reasoning of the basic principle of two-dimensional relational database, and presents a decision rules mining algorithm of information system based on rough set. The algorithm can select the decision rules on the basis of meeting the support and confidence, which can improve the accuracy and reasonableness of the decision rules mining.

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What this paper is about

There are many uncertainties of the data in information systems, which affects the extraction of decision rules. Using rough set to deal with these non-precise data can achieve effective decision-making rules by deleting redundant attributes. Through the relationship of key attributes, we can get association rules in a higher interested degree. The rules reflected the decision-making feature between attributes can provide decision support for policy-makers.This paper describes the implementation of rough set theory in incomplete data decision and reasoning of the basic principle of two-dimensional relational database, and presents a decision rules mining algorithm of information system based on rough set. The algorithm can select the decision rules on the basis of meeting the support and confidence, which can improve the accuracy and reasonableness of the decision rules mining.

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Available abstract

There are many uncertainties of the data in information systems, which affects the extraction of decision rules. Using rough set to deal with these non-precise data can achieve effective decision-making rules by deleting redundant attributes. Through the relationship of key attributes, we can get association rules in a higher interested degree. The rules reflected the decision-making feature between attributes can provide decision support for policy-makers.This paper describes the implementation of rough set theory in incomplete data decision and reasoning of the basic principle of two-dimensional relational database, and presents a decision rules mining algorithm of information system based on rough set. The algorithm can select the decision rules on the basis of meeting the support and confidence, which can improve the accuracy and reasonableness of the decision rules mining.

Key concepts: Rough set, Data mining, Computer science, Dominance-based rough set approach, Decision rule, Association rule learning, Key (lock), Set (abstract data type)

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