A heuristic framework for pivot-based bilingual dictionary induction

Mairidan Wushouer, Toru Ishida, Donghui Lin

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

4 Citations (Scopus)

Abstract

High quality machine readable dictionaries are very useful, but such resources are rarely available for lower-density language pairs, especially for those that are closely related. In this paper, we proposed a heuristic framework that aims at inducing one-to-one mapping dictionary of a closely related language pair from available dictionaries where a distant language is involved. The key insight of the framework is the ability to create heuristics by using distant language as pivot, incorporate given heuristics, and an iterative induction mechanism that human interaction can be potentially integrated. An experiment based on basic heuristics regarding syntactics and semantics resulted in up to 85.2% correctness in target dictionary with correctness of major part reached 95.3%, which proved that we can perform automated creation of a high quality dictionary with our framework.

Original languageEnglish
Title of host publicationProceedings - 2013 International Conference on Culture and Computing, Culture and Computing 2013
PublisherIEEE Computer Society
Pages111-116
Number of pages6
ISBN (Print)9780769550473
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 International Conference on Culture and Computing, Culture and Computing 2013 - Kyoto, Japan
Duration: 2013 Sept 162013 Sept 18

Publication series

NameProceedings - 2013 International Conference on Culture and Computing, Culture and Computing 2013

Conference

Conference2013 International Conference on Culture and Computing, Culture and Computing 2013
Country/TerritoryJapan
CityKyoto
Period13/9/1613/9/18

Keywords

  • Dictionary induction
  • Heuristics
  • Iterative framework
  • Pivot language

ASJC Scopus subject areas

  • Software

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