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
Citation
JIANG, Tao and TAN, Ah-hwee.
Mining RDF metadata for generalized association rules. (2006). Database and Expert Systems Applications: DEXA 2006, September 4-6, Krakow, Poland: Proceedings. 4080, 223-233.
Available at: https://ink.library.smu.edu.sg/sis_research/6574
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/11827405_22