中文摘要：

词语相似度计算是机器翻译、信息检索等自然语言处理领域的关键问题之一。传统的词语相似度计算方法，未能很好地考虑上下文信息对词语语义的约束，从而不能对语境变换带来的词语间相似度的差异进行有效的区分。该文引入模糊数学中隶属函数的概念计算词语上下文信息的模糊重要度，并结合基于《知网》的语义相似度计算方法，提出一种基于语境的词语相似度计算方法。实验表明，该算法可以根据语境有效地区分语义相近的词语。

英文摘要：

Word similarity computation is one of the key issues in natural language processing fields, such as machine translation, information retrieval etc. As traditional methods ignore the context information of the word, they can not effectively distinguish the differences among the word similarities when the context information changes. This paper presents an approach for word similarity computation based on the context information, which employs the fuzzy membership functions to compute the fuzzy significance of the words and combines a method of word similarity calculation using HowNet. The experimental results indicate that our approach distinguish the semantic similar words effectively by the context information.