Resolving error accumulation of automatically acquiring bilingual lexical knowledge by semantic similarity

While using a large-scale bilingual English-Chinese corpus to build translation dictionary, after some statistics and analysis, it is found that there are some unconquerable error accumulation problems while acquiring bilingual lexical knowledge by using large-scale bilingual corpus. Furthermore, a method is raised to solve this problem using semantic dictionary and its similarity measurement. Primary experiment has indicated that this method is effective and feasible. The application-oriented comparison between HowNet and WordNet has been made in this paper, and a conclusion is drawn: HowNet has higher recall while WordNet has higher precision for their difference of semantic granularity.