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作 者:刘丽珍[1] 赵新蕾[1] 王函石[1] 聂欣慧 宋巍[1]
出 处:《北京理工大学学报》2015年第5期538-544,共7页Transactions of Beijing Institute of Technology
基 金:国家自然科学基金资助项目(61303105&61402304);国家教育部人文社会科学研究资助项目(14YJAZH046);北京市自然科学基金资助项目(4154065);北京市教育委员会科技发展计划面上资助项目(KM201410028017)
摘 要:研究构建领域情感本体,显式描述产品与产品部件、产品与产品属性之间的语义关系;设计词性模式匹配方法提取特征词和情感词的固定搭配,并采用评论句的极性标签结合否定词典,逆向推测搭配组合的情感极性,建立特征词与情感词的关联关系;进一步设计本体节点匹配规则进行情感分析,提高对电商网站评论文本情感分析的性能.实验结果表明,领域情感本体的构建有利于消除情感词的领域依赖性及识别评论中的隐性特征.In order to improve the performance of sentiment analysis on the review texts of ecommerce sites,an approach was proposed to construct a domain affective ontology.The affective ontology,which was constructed,clearly described the semantic relation between a product and its components,aproduct and its attributes,as well as associations between product features and affective words.Particularly,collocations of feature words and affective words were extracted by POS patterns and their sentiment polarity was retroactively predicted by the polarity labels of review sentences and negations.Furthermore,node matching rules of ontology were put forward for sentiment analysis.The experimental results show that this domain affective ontology can provide the useful foundation for eliminating the domain-dependence of affective words and mining implicit features in product reviews.
分 类 号:TP391.1[自动化与计算机技术—计算机应用技术]
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