基于句子的多属性融合相似度计算方法  

Multi-attribute Fusion Similarity Calculation Method Based on Sentence

作　　者：袁绍正 周艳平[1] YUAN Shao-Zheng;ZHOU Yan-Ping(College of Information Science and Technology,Qingdao University of Science&Technology,Qingdao 266061,China)

机构地区：[1]青岛科技大学信息科学技术学院,青岛266061

出　　处：《计算机系统应用》2022年第4期303-308,共6页Computer Systems & Applications

摘　　要：针对现有的句子相似度计算方法没有考虑句子中的关键词的多属性信息,无法更好衡量句子相似度的问题,综合考虑句子的结构和包含的属性,提出一种基于句子的多属性融合相似度计算方法.该方法通过提取句子的词频属性、词序属性、词性属性及句长属性,采用层次分析法(AHP)计算出各属性的权重,并验证权重值的合理性,继而加权融合4种属性的相似度.将本文提出的多属性融合相似度计算方法在构建的数据集上进行实验,验证此方法的可靠性及可行性,并以召回率、准确率以及归一化F-度量值为标准和其他传统方法进行对比分析,结果表明,该方法不仅有着均衡的召回率和准确率,且F-度量值较高,达到83.57%.The current sentence similarity calculation method does not consider the multi-attributes of the keywords in the sentence and cannot better measure the sentence similarity. Therefore, this study proposes a sentence similarity calculation method based on multi-attribute fusion, considering the sentence structure and the attributes contained. First,this method extracts the attributes of the sentence including the word frequency, word order, part of speech, and sentence length. Next, the analytic hierarchy process(AHP) is used to calculate the weight of each attribute and verify the rationality of the weight, and then the weighted fusion of the similarity of the four attributes is conducted. This proposed calculation method for multi-attribute sentence similarity is tested on the constructed dataset to verify its reliability and feasibility, and it is compared with other traditional methods in recall rates, accuracy rates, and normalized F-measure values. The results show that this method has balanced recall and accuracy rates and a high F-measure value of 83.57%.

关 键 词：多属性 权重 句子相似度 层次分析法(AHP) F-度量值 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]