Mining RDF metadata for generalized association rules: Knowledge discovery in the semantic web era
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...
Saved in:
Main Authors: | JIANG, Tao, TAN, Ah-hwee |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2006
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/6696 https://ink.library.smu.edu.sg/context/sis_research/article/7699/viewcontent/1135777.1135960.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Mining generalized associations of semantic relations from textual web content
by: JIANG, Tao, et al.
Published: (2007) -
Mining RDF metadata for generalized association rules
by: JIANG, Tao, et al.
Published: (2006) -
Characterization of Singapore RDF resources and analysis of their heating value
by: Zhao, Lei, et al.
Published: (2016) -
A support-ordered trie for fast frequent itemset discovery
by: LIM, Ee Peng, et al.
Published: (2004) -
Efficient mining of intertransaction association rules
by: Tung, A.K.H., et al.
Published: (2013)