Parameter-free extended edit distance

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

Abstract

The edit distance is the most famous distance to compute the similarity between two strings of characters. The main drawback of the edit distance is that it is based on local procedures which reflect only a local view of similarity. To remedy this problem we presented in a previous work the extended edit distance, which adds a global view of similarity between two strings. However, the extended edit distance includes a parameter whose computation requires a long training time. In this paper we present a new extension of the edit distance which is parameter-free. We compare the performance of the new extension to that of the extended edit distance and we show how they both perform very similarly.

Original languageEnglish
Title of host publicationData Warehousing and Knowledge Discovery - 16th International Conference, DaWaK 2014, Proceedings
PublisherSpringer-Verlag Italia
Pages465-475
Number of pages11
ISBN (Electronic)978-3-319-10160-6
ISBN (Print)978-3-319-10159-0
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event16th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2014 - Munich, Germany
Duration: 2 Sep 20144 Sep 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8646 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2014
CountryGermany
CityMunich
Period2/09/144/09/14

Keywords

  • Edit Distance
  • Extended Edit Distance
  • Parameter-Free Extended Edit Distance

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Muhammad Fuad, M. M. (2014). Parameter-free extended edit distance. In Data Warehousing and Knowledge Discovery - 16th International Conference, DaWaK 2014, Proceedings (pp. 465-475). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8646 LNCS). Springer-Verlag Italia. https://doi.org/10.1007/978-3-319-10160-6_41