Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
5-2006
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 emphgeneralization closure for systematic over-generalization reduction.
Keywords
Association rule mining, RDF mining
Discipline
Numerical Analysis and Scientific Computing | Theory and Algorithms
Research Areas
Data Science and Engineering
Publication
WWW '06: Proceedings of the 15th International Conference on World Wide Web, May 23-26, Edinburgh
First Page
951
Last Page
952
ISBN
9781595933232
Identifier
10.1145/1135777.1135960
Publisher
ACM
City or Country
New York
Citation
JIANG, Tao and TAN, Ah-hwee.
Mining RDF metadata for generalized association rules: Knowledge discovery in the semantic web era. (2006). WWW '06: Proceedings of the 15th International Conference on World Wide Web, May 23-26, Edinburgh. 951-952.
Available at: https://ink.library.smu.edu.sg/sis_research/6696
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/10.1145/1135777.1135960