本文建立跨语言专利机读词典并在跨语言专利语料库的基础上研究语义消歧来解决跨语言专利中语言障碍问题。
A machine readable cross language dictionary was made to solve the language problems and at the mean time, ambiguity elimination was analyzed based on the cross language patent corpus.
提出了一种基于贝叶斯分类与机读词典的多义词排歧方法，通过小规模语料库的训练和歧义词在机读词典中的语义定义来完成歧义的消除。
A method based on the bayes and machine readable dictionary was proposed, which could disambiguate by the training of a small-scale corpus and the definition of semantic in machine dictionary.
提出了一种基于贝叶斯分类与机读词典的多义词排歧方法，通过小规模语料库的训练和歧义词在机读词典中的语义定义来完成歧义的消除。
A method based on the bayes and machine readable dictionary was proposed, which could disambiguate by the training of a small-scale corpus and the definition of semantic in machine dictionary.
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