Exploratory Mining and Pruning Optimizations of Constrained Associations Rules

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Exploratory Mining and Pruning Optimizations of Constrained Associations Rules (1998)

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by Raymond T. Ng , Laks V.S. Lakshmanan , Alex Pang , Jiawei Hah

Citations:

312 - 44 self

BibTeX

@INPROCEEDINGS{Ng98exploratorymining,
    author = {Raymond T. Ng and Laks V.S. Lakshmanan and Alex Pang and Jiawei Hah},
    title = {Exploratory Mining and Pruning Optimizations of Constrained Associations Rules},
    booktitle = {},
    year = {1998},
    pages = {13--24},
    publisher = {ACM Press}
}

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Abstract

From the standpoint of supporting human-centered discovery of knowledge, the present-day model of mining association rules suffers from the following serious shortcom- ings: (i) lack of user exploration and control, (ii) lack of focus, and (iii) rigid notion of relationships. In effect, this model functions as a black-box, admitting little user interaction in between. We propose, in this paper, an architecture that opens up the black-box, and supports constraintbased, human-centered exploratory mining of associations. The foundation of this architecture is a rich set of con- straint constructs, including domain, class, and $QL-style aggregate constraints, which enable users to clearly specify what associations are to be mined. We propose constrained association queries as a means of specifying the constraints to be satisfied by the antecedent and consequent of a mined association.

Keyphrases

pruning optimization constrained association rule exploratory mining association rule suffers model function little user interaction user exploration human-centered exploratory mining serious shortcom ings rich set human-centered discovery ql-style aggregate constraint association query con straint construct rigid notion present-day model

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