Mining RDF metadata for generalized association rules: knowledge discovery in the semantic web era

Authors:
Tao Jiang;Ah-Hwee Tan
Affiliations:
Nanyang Technological University, Nanyang Avenue, Singapore;Nanyang Technological University, Nanyang Avenue, Singapore
Venue:
Proceedings of the 15th international conference on World Wide Web
Year:
2006

Citing 2
Cited 2

Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Mining Generalized Association Rules

VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases

The Giraffe semantic web browser

Proceedings of the 12th international conference on Entertainment and media in the ubiquitous era
Mining Frequent Generalized Patterns for Web Personalization in the Presence of Taxonomies

International Journal of Data Warehousing and Mining

Quantified Score

Hi-index	0.00

Visualization

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.