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Resolving Translation Ambiguity and Target Polysemy in Cross-Language Information Retrieval+

並列摘要


This paper deals with translation ambiguity and target polysemy problems together. Two monolingual balanced corpora are employed to learn word co-occurrence for the purpose of translation ambiguity resolution and augmented translation restrictions for that of target polysemy resolution. Experiments show that the model achieves 62.92% monolingual information retrieval, which is 40.80% better than that of the select-all model. When target polysemy resolution is added, the retrieval performance represents approximately a 10.11% increase over that of the model which resolves translation ambiguity only.

參考文獻


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被引用紀錄


Hong, J. F. (2010). 詞義預測研究:以語料庫驅動的語言學研究方法 [doctoral dissertation, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2010.02757
Yang, C. (2009). 網路日誌空間情緒分析方法之研究 [doctoral dissertation, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2009.01026

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