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黄德根Huang Degen

教授

 博士生导师  硕士生导师
学位:博士
性别:男
毕业院校:大连理工大学
所在单位:计算机科学与技术学院
Email :

论文成果

Designing effective web mining-based techniques for OOV translation

发布时间:2019-03-11 点击次数:

论文类型:会议论文
收录刊物:Scopus、EI
摘要:Due to a limited coverage of the existing bilingual dictionary, it is often difficult to translate the Out-Of-Vocabulary terms (OOV) in many natural language processing tasks. In this paper, we propose a general cascade mining technique of three steps, it leverages OOV category to optimize the effectiveness of each step. OOV category based expansion policy is suggested to get more relevant mixed-language documents. OOV category based hybrid extraction approach is suggested to perform a robust extraction. A more flexible model combination based on OOV category is also suggested. Moreover, we conducted experiments to evaluate the effectiveness of each step and the overall performance of the mining technique. The experimental results show significantly performance improvement than the existing methods. ?2010 IEEE.