首页 | 官方网站   微博 | 高级检索  
     

面向智能客服的句子相似度计算方法
引用本文:纪明宇,王晨龙,安翔,牟伟晔.面向智能客服的句子相似度计算方法[J].计算机工程与应用,2019,55(13):123-128.
作者姓名:纪明宇  王晨龙  安翔  牟伟晔
作者单位:东北林业大学 信息与计算机工程学院,哈尔滨,150040;东北林业大学 信息与计算机工程学院,哈尔滨,150040;东北林业大学 信息与计算机工程学院,哈尔滨,150040;东北林业大学 信息与计算机工程学院,哈尔滨,150040
基金项目:中央高校基本科研业务费专项资金;国家自然科学青年科学基金
摘    要:针对金融领域中智能客服的句子相似度计算方法进行了研究。利用基于词性的分词纠正模型减少中文歧义词、金融相关词汇的分词错误;通过词向量方法和循环神经网络分别提取词语级和句子级的语义特征,并且得到句子向量;用融合层计算出句子向量间的差异特征;对差异特征进行降维和归一化得到句子相似度计算结果。实验结果表明,该方法具有较高的准确率和F1值。

关 键 词:智能客服  句子相似度  分词纠正  词向量  循环神经网络

Method of Sentence Similarity Calculation for Intelligent Customer Service
JI Mingyu,WANG Chenlong,AN Xiang,MU Weiye.Method of Sentence Similarity Calculation for Intelligent Customer Service[J].Computer Engineering and Applications,2019,55(13):123-128.
Authors:JI Mingyu  WANG Chenlong  AN Xiang  MU Weiye
Affiliation:School of Information and Computer Engineering, University of Northeast Forestry, Harbin 150040, China
Abstract:In view of sentence similarity calculation method for intelligent customer service in financial field is studied. Firstly, it reduces the participle errors of Chinese ambiguous words and financial related words by the participle correction model based on part-of-speech. Then, it extracts the semantic features of word level and sentence level and obtains the sentence vectors by the method of word vector and circulatory neural network. In addition, it calculates the discriminative features between sentence vectors by the merge layer. Finally, it obtains the result of sentence similarity calculation by dimension reduction and normalization of the discriminative features. Experiments show that this method has high accuracy and F1 value.
Keywords:intelligent customer service  sentence similarity  participle correction  word vector  cyclic neural network  
本文献已被 维普 万方数据 等数据库收录!
点击此处可从《计算机工程与应用》浏览原始摘要信息
点击此处可从《计算机工程与应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号