Bounded occurrence edit distance: A new metric for string similarity joins with edit distance constraints

Tomoki Komatsu, Ryosuke Okuta, Kazuyuki Narisawa, Ayumi Shinohara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Given two sets of strings and a similarity function on strings, similarity joins attempt to find all similar pairs of strings from each respective set. In this paper, we focus on similarity joins with respect to the edit distance, and propose a new metric called the bounded occurrence edit distance and a filter based on the metric. Using the filter, we can reduce the total time required to solve similarity joins because the metric can be computed faster than the edit distance by bitwise operations. We demonstrate the effectiveness of the filter through experiments.

Original languageEnglish
Title of host publicationSOFSEM 2014
Subtitle of host publicationTheory and Practice of Computer Science - 40th International Conference on Current Trends in Theory and Practice of Computer Science, Proceedings
PublisherSpringer Verlag
Pages363-374
Number of pages12
ISBN (Print)9783319042978
DOIs
Publication statusPublished - 2014
Event40th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2014 - Novy Smokovec, Slovakia
Duration: 2014 Jan 262014 Jan 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8327 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other40th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2014
CountrySlovakia
CityNovy Smokovec
Period14/1/2614/1/29

Keywords

  • Data integration
  • Edit distance
  • Similarity join problem
  • Similarity search

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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