Transliteration retrieval model for cross lingual information retrieval

Ea Ee Jan, Shih Hsiang Lin, Berlin Chen

研究成果: 書貢獻/報告類型會議論文篇章

1 引文 斯高帕斯(Scopus)


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.

主出版物標題Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings
出版狀態已發佈 - 2010 十二月 1
事件6th Asia Information Retrieval Societies Conference, AIRS 2010 - Taipei, 臺灣
持續時間: 2010 十二月 12010 十二月 3


名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6458 LNCS


其他6th Asia Information Retrieval Societies Conference, AIRS 2010

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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