摘要
该文提出了一种面向商品评论的二元情感认知模型。该模型由"二元情感常识库"、"评价体系知识库"和"情感分析引擎"三个主要模块组成。其特点体现为:(1)模型通过大规模评论文本学习领域先验知识,将其存储在知识库中,便于知识的修正和重用,体现了模型的认知能力;(2)模型不仅能够挖掘评论文本中出现的显式评价观点,还能借助领域知识进行情感推断,发现更高层次的用户情感。该文给出了构建"二元情感常识库"和"评价体系知识库"的相关算法,并介绍了"情感分析引擎"在观点挖掘和情感推断中的应用。在商品评论语料集上的实验验证了该模型的有效性。
This paper proposes a binary affective cognitive model for product reviews,which consists of three main modules：binary affective commonsense knowledge base,evaluation system knowledge base and sentiment analysis engine.This model has following characteristics：（1）It can learn the prior knowledge from large-scale reviews,and save it in the knowledge bases.These databases make it easier to revise and reuse knowledge,which embodies the cognitive ability of the model.（2）This model is able to reveal explicit opinions and infer high level sentiments.This paper gives the algorithms of constructing binary affective commonsense knowledge base and evaluation system knowledge base,and introduces the application of emotional analysis engine in opinion mining and sentiment inference.The experiment on product review corpus verifies the validity of the model.
作者
陈放
王颗
梁爽
黄永峰
CHEN Fang;WANG Ke;LIANG Shuang;HUANG Yongfeng(New Generation Network Technology and Application Laboratory,Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)
出处
《中文信息学报》
CSCD
北大核心
2018年第8期135-142,共8页
Journal of Chinese Information Processing
基金
国家自然科学基金(U1536201
U1536207)
关键词
情感认知
情感常识
评价体系
affective cognitions affective commonsense
evaluation system
