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Using an integrated feature set to generalize and justify the Chinese-to-English transferring rule of the 'ZHE' aspect

引用

Journal of Zhejiang University-Science C(Computers and Electronics) 2010年第9期11卷 663-676页

作者： Yun-hua QU Tian-jiong TAO Serge SHAROFF Narisong JIN Ruo-yuan GAO Nan ZHANG Yu-ting YANG Cheng-zhi XU School of International Studies Zhejiang University Hangzhou 310058 China Institute of Fluid Physics China Academy of Engineering Physics Mianyang 621900 China Center for Translation Studies University of Leeds Leeds LS2 9JT UK Center for Applied Linguistics Hangzhou Normal University Hangzhou 310012 China School of Computer Science and Technology Zhejiang University Hangzhou 310027 China Sensor Network and Application Research Center Graduate School Chinese Academy of Sciences Beijing 100049 China School of Economics Zhejiang University Hangzhou 310027 China Zhejiang University City College Hangzhou 310015 China

In machine translation(MT) practice,there is an urgent need for constructing a set of Chinese-to-English aspect transferring rules to define the transferring *** integrated feature set was used to generalize and justify the Chinese-to-English transferring rule of the 'ZHE' aspect(ZHE Rule).A ZHE classification model was built in this *** impacts of each set of temporal,lexical aspectual,and syntactic features,and their integrated impacts,on the accuracy of the ZHE Rule were *** 600 misclassified corpus sentences were manually examined.A 10-fold cross-validation was used with a decision tree *** main results are:(1) The ZHE Rule was generalized and justified to have a higher accuracy under the two metrics:the precision rate and the areas under the receiver operating characteristic curve(AUC).(2) The temporal,lexical aspectual,and syntactic feature sets have an integrated contribution to the accuracy of the ZHE *** syntactic and temporal features have an impact on ZHE aspect derivations,while the lexical aspectual features are not predictive of ZHE aspect derivation.(3) While associated with active verbs,the ZHE aspect can denote a perfective *** study suggests that the temporal and syntactic features are the predictive ZHE aspect classification features and that the ZHE Rule with an overall precision rate of 80.1% is accurate enough to be further explored in MT *** machine learning method,decision tree,can be applied to the automatic aspect transferring in MT research and aspectual interpretations in linguistic research.

关键词： ZHE aspect transferring rule(ZHE Rule) Machine learning Decision tree Aspect classification integrated feature set

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