Syntax-Based Aspect Sentiment Quad Prediction by Dual Modules Neural Network for Chinese Comments
作者机构:College of Information and Communication EngineeringCommunication University of ChinaDingfuzhuang East Street No.1Beijing100024China Cybersecurity and Criminology CentreUniversity of West LondonSt.Mary’s RoadLondon W55RFLondonUK Department of Electronic EngineeringTsinghua UniversityShuangqing Road No.30Beijing100084China The State Key Laboratory of Media Convergence and CommunicationCommunication University of ChinaDingfuzhuang East Street No.1Beijing100024China
出 版 物:《Computers, Materials & Continua》 (计算机、材料和连续体(英文))
年 卷 期:2023年第75卷第5期
页 面:2873-2888页
核心收录:
学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0805[工学-材料科学与工程(可授工学、理学学位)] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:supported by the National Key Research and Development Program(No.2021YFF0901705,2021YFF0901700) the StateKey Laboratory ofMedia Convergence and Communication,Communication University of China the Fundamental Research Funds for the Central Universities the High-quality and Cutting-edge Disciplines Construction Project for Universities in Beijing(Internet Information,Communication University of China)
主 题:ABSA ASQP sentiment analysis Chinese comments
摘 要:Aspect-Based Sentiment Analysis(ABSA)is one of the essential research in the field of Natural Language Processing(NLP),of which Aspect Sentiment Quad Prediction(ASQP)is a novel and complete *** aims to accurately recognize the sentiment quad in the target sentence,which includes the aspect term,the aspect category,the corresponding opinion term,and the sentiment polarity of ***,existing approaches lack knowledge of the sentence’s syntax,so despite recent innovations in ASQP,it is poor for complex cyber comment ***,most research has focused on processing English text,and ASQP for Chinese text is almost *** usage is more casual than English,and individual characters contain more *** propose a novel syntactically enhanced neural network framework inspired by syntax knowledge enhancement strategies in other NLP *** this framework,part of speech(POS)and dependency trees are input to the model as auxiliary information to strengthen its cognition of Chinese text ***,we design a relation extraction module,which provides a bridge for the overall extraction of the framework.A comparison of the designed experiments reveals that our proposed strategy outperforms the previous studies on the key metric *** experiments demonstrate that the auxiliary information added to the framework improves the final performance in different ways.