Mining with Constraints by Pruning and Avoiding Ineffectual Processing | Zendy

Mohammad El-Hajj | Zendy; Osmar R. Zaı̈ane | Zendy

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Mining with Constraints by Pruning and Avoiding Ineffectual Processing

Author(s) -

Mohammad El-Hajj,

Osmar R. Zaı̈ane

Publication year - 2005

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-30462-2

DOI - 10.1007/11589990_129

Subject(s) - computer science , pruning , set (abstract data type) , association rule learning , dual (grammatical number) , data mining , algorithm , theoretical computer science , programming language , art , literature , agronomy , biology

It is known that algorithms for discovering association rules generate an overwhelming number of those rules. While many new very efficient algorithms were recently proposed to allow the mining of extremely large datasets, the problem due to the sheer number of rules discovered still remains. In this paper we propose a new way of pushing the constraints in dual-mode based from the set of maximal patterns that is an order of magnitude smaller than the set of all frequent patterns.

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