Transliterated Word Identification and Application to Query Translation Mining

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DOI: 10.4236/jsea.2009.22018   PDF        4,674 Downloads   8,285 Views  

Abstract

Query translation mining is a key technique in cross-language information retrieval and machine translation knowl-edge acquisition. For better performance, the queries are classified into transliterated words and non-transliterated words based on transliterated word identification model, and are further channeled to different mining processes. This paper is a pilot study on query classification for better translation mining performance, which is based on supervised classification and linguistic heuristics. The person name identification gets a precision of over 97%. Transliterated word translation mining shows satisfactory performance.

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J. Zhang, L. Guo, M. Zhou and J. Yao, "Transliterated Word Identification and Application to Query Translation Mining," Journal of Software Engineering and Applications, Vol. 2 No. 2, 2009, pp. 122-126. doi: 10.4236/jsea.2009.22018.

Conflicts of Interest

The authors declare no conflicts of interest.

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