Cross Language Information Retrieval Using Parallel Corpus with Bilingual Mapping Method

Rinaldi Andrian Rahmanda, Mirna Adriani, Dipta Tanaya

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

Abstract

This study presents an approach to generate a bilingual language model that will be used for CLIR task. Language models for Bahasa Indonesia and English are created by utilizing a bilingual parallel corpus, and then the bilingual language model is created by learning the mapping between the Indonesian model and the English model using the Multilayer Perceptron model. Query expansion is also used in this system to boost the results of the retrieval, using pre-Bilingual Mapping, post-Bilingual Mapping and hybrid approaches. The results of the experiments show that the implemented system, with the addition of pre-Bilingual Mapping query expansion, manages to improve the performance of the CLIR task.

Original languageEnglish
Title of host publicationProceedings of the 2019 International Conference on Asian Language Processing, IALP 2019
EditorsMan Lan, Yuanbin Wu, Minghui Dong, Yanfeng Lu, Yan Yang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages222-227
Number of pages6
ISBN (Electronic)9781728150147
DOIs
Publication statusPublished - Nov 2019
Event23rd International Conference on Asian Language Processing, IALP 2019 - Shanghai, China
Duration: 15 Nov 201917 Nov 2019

Publication series

NameProceedings of the 2019 International Conference on Asian Language Processing, IALP 2019

Conference

Conference23rd International Conference on Asian Language Processing, IALP 2019
CountryChina
CityShanghai
Period15/11/1917/11/19

Keywords

  • Bilingual Mapping
  • Cross Language Information Retrieval
  • Language Model
  • Multilayer Perceptron
  • parallel corpus

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