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Bilingual seed lexicon adaptation for entity translation extraction

  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Bilingual seed lexicon, which is considered as a bridge between two languages, is one of the main resources used for entity translation extraction tasks from comparable corpora. However, little attention has been paid to this lexicon except its coverage. In fact, the quality of the seed lexicon is one of the key factors that affect the accuracy of entity translation extraction. In this paper, we propose a new self-adaptive model. We use a word segmentation technique to adapt segmented corpora and then propose two strategies of weight allocation and corresponding filter. Experiments demonstrate that our technique significantly outperforms the standard approach.

Original languageEnglish
Title of host publicationProceedings - 2013 9th International Conference on Natural Computation, ICNC 2013
PublisherIEEE Computer Society
Pages1309-1313
Number of pages5
ISBN (Print)9781467347143
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 9th International Conference on Natural Computation, ICNC 2013 - Shenyang, China
Duration: 23 Jul 201325 Jul 2013

Publication series

NameProceedings - International Conference on Natural Computation
ISSN (Print)2157-9555

Conference

Conference2013 9th International Conference on Natural Computation, ICNC 2013
Country/TerritoryChina
CityShenyang
Period23/07/1325/07/13

Keywords

  • adaptation
  • comparable corpora
  • entity translation extraction
  • seed lexicon

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