基于主题和关键词特征的比较文本分类方法  

Comparative Text Classification Method Based on Topic and Keyword Feature

作　　者：丁勇[1,2] 程家桥[1] 蒋翠清 王钊[1,2] DING Yong;CHENG Jiaqiao;JIANG Cuiqing;WANG Zhao(School of Management,Hefei University of Technology,Hefei 230009,China;Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education,Hefei 230009,China)

机构地区：[1]合肥工业大学管理学院,合肥230009 [2]过程优化与智能决策教育部重点实验室,合肥230009

出　　处：《计算机工程与应用》2021年第17期196-202,共7页Computer Engineering and Applications

基　　金：国家自然科学基金重点项目(71731005);教育部人文社会科学规划基金项目(15YJA630010)。

摘　　要：比较文本对于企业竞争产品分析至关重要,但目前面向问答领域的比较文本分类研究较少。针对问答文本中比较信息丰富、主题集中的特点,提出了基于主题特征和关键词特征扩展的比较文本分类方法。通过预训练主题模型,推断问答文本的主题概率分布作为其主题特征;针对向量拼接、求和导致关键词信息流失的问题,设计GRU自编码器实现关键词向量特征提取。综合文本主题信息和关键词语义,从语言、产品、情感、社交、主题、关键词角度构建比较文本分类特征,最后使用多种分类器对问答文本进行分类。实验结果表明,构建的特征行之有效,比较文本分类效果较好。Comparative text is very important for competitive products analysis,but there are few researches on the classification of comparative text in the Q&A field.Aiming at the characteristics of rich information and concentrated topics in Q&A texts,this paper proposes a comparative text classification method based on topic feature and keyword feature expansion.Based on the pretrained topic model,the topic probability distribution of the Q&A text is inferred as its topic feature.In view of the keyword information loss caused by vector concatenation and summation,GRU-autoencoder is designed to realize feature extraction,and the encoder output is used as the keyword feature of Q&A text.Integrating the topic information and keyword semantics,the comparative text features are constructed from the perspectives of linguistics,product,sentiment,social,topic and keyword,then the Q&A text is classified by using various classifiers.The experimental results show that the constructed features are effective and the effect of the classification are better.

关 键 词：主题模型 自编码器 特征扩展 比较文本分类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]