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Machine translation method decomposing compound noun using markov model

机译:用马尔可夫模型分解复合名词的机器翻译方法

摘要

PURPOSE: A machine translation method is provided to separate a compound noun by statistically analyzing the compound noun and designing and learning a Markov model thereof. CONSTITUTION: The machine translation method includes a morpheme analyzing step, a tagging step, an idiom processing step, a vocabulary pre-processing step, a conversion rule application step, a meaning vagueness solving step, and an object language generating step. A compound noun is separated to process the compound noun registered in the vocabulary pre-processing step. The compound noun separating step includes a mechanical learning step and a separating step. In the separating step, the compound noun is separated from using a separating algorithm by using a mechanical learning data of the mechanical learning step.
机译:目的:提供一种机器翻译方法,通过对复合名词进行统计分析并设计和学习其马尔可夫模型来分离复合名词。组成:机器翻译方法包括一个词素分析步骤,一个标记步骤,一个成语处理步骤,一个词汇预处理步骤,一个转换规则应用步骤,一个含义模糊性解决步骤和一个目标语言生成步骤。分离复合名词以处理在词汇预处理步骤中注册的复合名词。复合名词分离步骤包括机械学习步骤和分离步骤。在分离步骤中,通过使用机械学习步骤的机械学习数据,使用分离算法将复合名词分离。

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