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Learning weights for translation candidates in Japanese-Chinese information retrieval
Abstract This paper describes our Japanese-Chinese This paper describes our Japanese-Chinese information retrieval system. Our system takes the query-translation" approach. Our system employs both a more conventional bilingual Japanese-Chinese dictionary and Wikipedia for translating query terms. We propose that Wikipedia can be used as a good NE bilingual dictionary. By exploiting the nature of Japanese writing system we propose that query terms be processed differently based on the forms they are written in. We use an iterative method for weight-tuning and term disambiguation which is based on the PageRank algorithm. When evaluating on the NTCIR-5 test set our system achieves as high as 0.2217 and 0.2276 in relax MAP (mean average precision) measurement of T-runs and D-runs.ecision) measurement of T-runs and D-runs.
Added by wikilit team Added on initial load  +
Collected data time dimension Cross-sectional  +
Conclusion We exploited the nature of Japanese vocabuWe exploited the nature of Japanese vocabulary and the Japanese writing system for better translations. Using Kanji for translation yields significant improvements in our evaluation. The results of the evaluation confirm that foreign terms are widely transcribed in Katakana. To cope with ambiguity, we have adopted an iterative disambiguating scheme. The current implementation of this scheme, which uses the likelihood function as its weight function, proved to be effective in the evaluation. Our system has achieved MAP as high as 0.2276, and outperforms the previous NTCIR-5 CLIR Japanese–Chinese T-run’s best rigid MAP by 111%, and D-run’s by 19%.est rigid MAP by 111%, and D-run’s by 19%.
Data source Documents  + , Wikipedia pages  +
Doi 10.1016/j.eswa.2008.09.004 +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22Learning%2Bweights%2Bfor%2Btranslation%2Bcandidates%2Bin%2BJapanese-Chinese%2Binformation%2Bretrieval%22  +
Has author Chu-Cheng Lin + , Yu-Chun Wang + , Chih-Hao Yeh + , Wei-Chi Tsai + , Richard Tzong-Han Tsai +
Has domain Computer science +
Has topic Cross-language information retrieval +
Issue 4  +
Pages 7695-7699  +
Peer reviewed Yes  +
Publication type Journal article  +
Published in Expert Systems with Applications +
Research design Mathematical modeling  + , Statistical analysis  +
Research questions his paper describes our Japanese–Chinese ihis paper describes our Japanese–Chinese information retrieval system. Our system takes the “query-translation” approach. Our system employs both a more conventional bilingual Japanese–Chinese dictionary and Wikipedia for translating query terms. We propose that Wikipedia can be used as a good NE bilingual dictionary. By exploiting the nature of Japanese writing system, we propose that query terms be processed differently based on the forms they are written in. We use an iterative method for weight-tuning and term disambiguation, which is based on the PageRank algorithm. which is based on the PageRank algorithm.
Revid 10,852  +
Theories Undetermined
Theory type Design and action  +
Title Learning weights for translation candidates in Japanese-Chinese information retrieval
Unit of analysis Article  +
Url http://dx.doi.org/10.1016/j.eswa.2008.09.004  +
Volume 36  +
Wikipedia coverage Sample data  +
Wikipedia data extraction Live Wikipedia  +
Wikipedia language Chinese  + , Japanese  +
Wikipedia page type Article  +
Year 2009  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:29:28  +
Categories Cross-language information retrieval  + , Computer science  + , Publications with missing comments  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:29:25  +
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