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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/1427

Title: Mining For Tree-Query Associations In A Graph
Authors: HOEKX, Eveline
Issue Date: 2006
Publisher: IEEE Computer Society 2006
Citation: Clifton, CW & Zhong, N & Liu, JM & Wah, BW & Wu, XD (Ed.) Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006). p. 254-264.
Series/Report: IEEE International Conference on Data Mining
Abstract: New applications of data mining, such as in biology, bioinformatics, or sociology, are faced with large datasets structured as graphs. We present an efficient algorithm for mining associations between tree queries in a large graph. Tree queries are powerful tree-shaped patterns featuring existential variables and data constants. Our algorithm applies the theory of conjunctive database queries to make the generation of association rules efficient. We propose a practical, database-oriented implementation in SQL, and show that the approach works in practice through experiments on data about food webs, protein interactions, and citation analysis.
URI: http://hdl.handle.net/1942/1427
DOI: 10.1109/ICDM.2006.107
ISI #: 000245601900027
ISBN: 978-0-7695-2701-7
ISSN: 1550-4786
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2008
Appears in Collections: Research publications

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