Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

9-2006

Abstract

In this paper, we present a novel frequent generalized pattern mining algorithm, called GP-Close, for mining generalized associations from RDF metadata. To solve the over-generalization problem encountered by existing methods, GP-Close employs the notion of generalization closure for systematic over-generalization reduction. Empirical experiments conducted on real world RDF data sets show that our method can substantially reduce pattern redundancy and perform much better than the original generalized association rule mining algorithm Cumulate in term of time efficiency.

Keywords

Association Rule, Resource Description Framework, Terrorist Group, Resource Description Framework Data, Root Closure

Discipline

Theory and Algorithms

Research Areas

Data Science and Engineering

Publication

Database and Expert Systems Applications: DEXA 2006, September 4-6, Krakow, Poland: Proceedings

Volume

4080

First Page

223

Last Page

233

ISBN

9783540378716

Identifier

10.1007/11827405_22

Publisher

Springer

City or Country

Cham

Additional URL

https://doi.org/10.1007/11827405_22

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