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Combining Common Words And Semantic Features For Sentence Similarity

机译：结合句子相似性的常见词和语义特征

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Assessing the similarity of short texts or sentences is an important phase in many natural processing activities. The paper describes the importance and role of sentence similarity in various domains and also the paper provides a mechanism to calculate the similarity between short texts. The main idea in this paper is to extract the syntactic and semantic features between the sentences, to calculate the similarity between them. The syntactic features are evaluated by finding the common words between the sentences, whereas the semantic features are evaluated using the information content between the concepts of the sentences. For obtaining the information content between the concepts knowledge based measures are used. Three information content based measures are compared in this paper over bench mark sentence similarity dataset. The results show that the integration of syntactic and semantic features increases the performance of the system.
机译：评估短文本或句子的相似性是许多自然加工活动的重要阶段。本文介绍了句子相似性在各个域中的重要性和作用，以及该文件提供了一种计算短文本之间相似性的机制。本文的主要思想是提取句子之间的句法和语义特征，以计算它们之间的相似性。通过查找句子之间的常用词来评估句法特征，而使用句子的概念之间的信息内容进行评估语义特征。为了获得基于概念之间的信息内容，使用了基于知识的措施。在这篇论文中，在替补标记句子相似度数据集中比较了三种信息基于内容的措施。结果表明，句法和语义功能的集成会增加系统的性能。

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