Transliteration retrieval model for cross lingual information retrieval

Ea Ee Jan, Shih Hsiang Lin, Berlin Chen

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

1 Citation (Scopus)

Abstract

The performance of transliteration from a source language to a target language builds the ground work in support of proper name Cross Lingual Information Retrieval (CLIR). Traditionally, this task is accomplished by two separate modules: transliteration and retrieval. Queries are first transliterated to target language using one or multiple hypotheses. The retrieval is then carried out based on translated queries. The transliteration often results in 30-50% errors with top 1 hypothesis, thus leading to significant performance degradation in CLIR. Therefore, we proposed a unified transliteration retrieval model that incorporates the transliteration similarity measurement into the relevance scoring function. In addition, we presented an efficient and robust method in similarity measurement for a given proper name pair using the Hidden Markov Model (HMM) based alignment and a Statistical Machine Translation (SMT) framework. Experimental data showed significant results with the proposed integrated method on the NTCIR7 IR4QA task, which demonstrated a greater flexibility and acceptance in transliteration.

Original languageEnglish
Title of host publicationInformation Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings
Pages183-192
Number of pages10
DOIs
Publication statusPublished - 2010 Dec 1
Event6th Asia Information Retrieval Societies Conference, AIRS 2010 - Taipei, Taiwan
Duration: 2010 Dec 12010 Dec 3

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6458 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th Asia Information Retrieval Societies Conference, AIRS 2010
CountryTaiwan
CityTaipei
Period10/12/110/12/3

Keywords

  • NTCIR
  • cross lingual information retrieval (CLIR)
  • retrieval model
  • statistical machine translation (SMT)
  • transliteration

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Jan, E. E., Lin, S. H., & Chen, B. (2010). Transliteration retrieval model for cross lingual information retrieval. In Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings (pp. 183-192). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6458 LNCS). https://doi.org/10.1007/978-3-642-17187-1_17