A cost-effective LSH filter for fast pairwise mining

Zhao, G; Xiong, Y; Cao, L; Luo, D; Su, X; Zhu, Y

A cost-effective LSH filter for fast pairwise mining

Zhao, G Xiong, Y Cao, L

Luo, D Su, X Zhu, Y

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Publication Type:: Conference Proceeding
Citation:: Proceedings - IEEE International Conference on Data Mining, ICDM, 2009, pp. 1088 - 1093
Issue Date:: 2009-12-01

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Field	Value	Language
dc.contributor.author	Zhao, G	en_US
dc.contributor.author	Xiong, Y	en_US
dc.contributor.author	Cao, L https://orcid.org/0000-0003-1562-9429	en_US
dc.contributor.author	Luo, D	en_US
dc.contributor.author	Su, X	en_US
dc.contributor.author	Zhu, Y	en_US
dc.date.issued	2009-12-01	en_US
dc.identifier.citation	Proceedings - IEEE International Conference on Data Mining, ICDM, 2009, pp. 1088 - 1093	en_US
dc.identifier.isbn	9780769538952	en_US
dc.identifier.issn	1550-4786	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11911
dc.description.abstract	The pairwise mining problem is to discover pairwise objects having measures greater than the user-specified minimum threshold from a collection of objects. It is essential in a large variety of database and data-mining applications. Of late, there has been increasing interest in applying a Locality- Sensitive Hashing (LSH) scheme for pairwise mining. LSH-type methods have shown themselves to be simply implementable and capable of achieving significant performance gain in running time over most exact methods. However, the present LSH-type methods still suffer from some bottlenecks, such as "the curse of threshold". In this paper, we proposed a novel LSH-based method, namely Cost-effective LSH filter (Ce-LSH for short), for pairwise mining. Compared with previous LSH-type methods, it uses a lower fixed number of LSH functions and is thus more cost-effective. Substantial experiments evidence that our method gives significant improvement in running time over existing LSH-type methods and some recently reported method based on upper-bound. Experimental results also indicate that it scales well even for a relatively low minimum threshold and for a fairly small miss ratio. © 2009 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0667060
dc.relation	http://purl.org/au-research/grants/arc/DP0773412
dc.relation	http://purl.org/au-research/grants/arc/DP0988016
dc.relation.ispartof	Proceedings - IEEE International Conference on Data Mining, ICDM	en_US
dc.relation.isbasedon	10.1109/ICDM.2009.112	en_US
dc.title	A cost-effective LSH filter for fast pairwise mining	en_US
dc.type	Conference Proceeding
utslib.for	080110 Simulation and Modelling	en_US
utslib.for	0804 Data Format	en_US
dc.location.activity	Miami, Florida, USA	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

The pairwise mining problem is to discover pairwise objects having measures greater than the user-specified minimum threshold from a collection of objects. It is essential in a large variety of database and data-mining applications. Of late, there has been increasing interest in applying a Locality- Sensitive Hashing (LSH) scheme for pairwise mining. LSH-type methods have shown themselves to be simply implementable and capable of achieving significant performance gain in running time over most exact methods. However, the present LSH-type methods still suffer from some bottlenecks, such as "the curse of threshold". In this paper, we proposed a novel LSH-based method, namely Cost-effective LSH filter (Ce-LSH for short), for pairwise mining. Compared with previous LSH-type methods, it uses a lower fixed number of LSH functions and is thus more cost-effective. Substantial experiments evidence that our method gives significant improvement in running time over existing LSH-type methods and some recently reported method based on upper-bound. Experimental results also indicate that it scales well even for a relatively low minimum threshold and for a fairly small miss ratio. © 2009 IEEE.

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http://hdl.handle.net/10453/11911