计算机科学 ›› 2011, Vol. 38 ›› Issue (8): 239-241.

• 人工智能 • 上一篇    下一篇

基于多尺度句子信息的语义距离计算

王忠林   

  1. (中国电子科技集团公司第12研究所大功率微波电真空器件技术国防科技重点实验室 北京100015)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Semantic Calculation Framework Based on Multiscale Analysis

WANG Zhong-lin   

  • Online:2018-11-16 Published:2018-11-16

摘要: 句子语义距离计算是许多智能系统的一项基础技术。基于多尺度分析思想,提出一个多级语义距离计算方法。首先通过词汇级语义距离算法对句子对进行初步过滤,然后对于语义距离小于一定阂值的例子进行语法分析、语义分析;获得标准语义分析框架之后,再次对框架中的中心概念进行比较,最后对通过二级筛选的句子对使用基于动态权重的语义同构算法进行计算,得到最终的语义距离。最后通过实验验证,该方法总精度达到73.3%,对相关度比较高的情况,到达和基于语义级算法相近的91. 4%。

关键词: 语义距离,多尺度分析,词汇级,语义级

Abstract: The calculation of the sentence semantic distance acts a base role in many intelligent systems. Based on multi-scale analysis,a multi level semantic distance calculation framework was proposed. All sentence pairs were filtered by word-level semantic distance algorithm first, and then syntax parsing and semantic parsing were executed for the sentence pairs which semantic distances were below the threshold. After getting the standard semantic frameworks, the core conceptions in the frameworks were compared then. The final semantic distances of the sentence pairs passing the second level filter were obtained using isomorphism-based semantic distance algorithm,which could dynamically adjust its weights. Experiments show that the total precision of the method reaches 73.3%. For the cases, it has higher relevance, reaches 91.4%,similar to the semantic-level algorithm.

Key words: Semantic distance, Multiscale analysis, Word-level, Semantic level

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