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 
VAN DEN BUSSCHE, Jan 
Issue Date: 2006
Publisher: IEEE Computer Society 2006
Source: 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.
Keywords: data mining, bioinformatics, databases, conjunctive queries, graph queries, tree queries
Document URI: http://hdl.handle.net/1942/1427
ISBN: 978-0-7695-2701-7
DOI: 10.1109/ICDM.2006.107
ISI #: 000245601900027
Category: C1
Type: Proceedings Paper
Validations: ecoom 2008
Appears in Collections:Research publications

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