PartSS : An efficient partition-based filtering for edit distance constraints

Li, Zhixu, Sitbon, Laurianne, & Zhou, Xiaofang (2011) PartSS : An efficient partition-based filtering for edit distance constraints. In Shen, Heng Tao & Zhang, Yanchun (Eds.) Australasian Database Conference (ADC 2011), ACS, Perth, Australia , 103-112 .

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Abstract

This paper introduces PartSS, a new partition-based fil- tering for tasks performing string comparisons under edit distance constraints. PartSS offers improvements over the state-of-the-art method NGPP with the implementation of a new partitioning scheme and also improves filtering abil- ities by exploiting theoretical results on shifting and scaling ranges, thus accelerating the rate of calculating edit distance between strings. PartSS filtering has been implemented within two major tasks of data integration: similarity join and approximate membership extraction under edit distance constraints. The evaluation on an extensive range of real-world datasets demonstrates major gain in efficiency over NGPP and QGrams approaches.

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ID Code: 56386
Item Type: Conference Paper
Refereed: Yes
Keywords: edit distance, partition-based, similarity join, approximate membership extraction
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Natural Language Processing (080107)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTATION THEORY AND MATHEMATICS (080200) > Analysis of Algorithms and Complexity (080201)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2011 Australian Computer Society, Inc.
Copyright Statement:

Copyright 2011, Australian Computer Society, Inc.

This paper appeared at the 22nd Australasian Database Conference (ADC 2011), Perth, Australia, January 2011. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 115, Heng Tao Shen and Yanchun Zhang, Ed.

Reproduction for academic, not-for-profit purposes permitted provided this text is included.

Deposited On: 11 Jan 2013 02:14
Last Modified: 09 Apr 2013 08:57

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