Generating Domain-Specific Affective Ontology from Chinese Reviews for Sentiment Analysis

被引:0
|
作者
刘丽珍 [1 ]
刘昊 [1 ]
王函石 [1 ]
宋巍 [1 ]
赵新蕾 [1 ]
机构
[1] College of Information Engineering, Capital Normal University
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
affective ontology; sentimentanalysis; product features; Chinese reviews;
D O I
暂无
中图分类号
TP391.1 [文字信息处理];
学科分类号
081203 ; 0835 ;
摘要
Considering the diversities and ambiguities of opinion expressions in Chinese online product reviews,normal sentiment analysis technologies have exposed their inadequateness in both classification accuracy and identifying effectiveness.We propose a novel approach which can easily identify product features and corresponding opinions by building a domain-specific affective ontology and thus mapping comment sentences to the objects defined in the affective ontology.Ontology is created automatically by processing the online reviews;both product features and affective words are presented as nodes which are connected to each other by their semantic relationship.Furthermore,in order to increase the accuracy,we introduce a dynamic polarity detection technique for affective words whose sentimental tendencies are dependent on particular contexts.The experimental results clearly demonstrate the performance improvement of our approach compared with others in real world online product reviews for classification tests.
引用
收藏
页码:32 / 37
页数:6
相关论文
共 50 条
  • [21] Domain-specific sentiment classification via fusing sentiment knowledge from multiple sources
    Wu, Fangzhao
    Huang, Yongfeng
    Yuan, Zhigang
    [J]. INFORMATION FUSION, 2017, 35 : 26 - 37
  • [22] Sentiment Analysis Across Languages Based on Domain-Specific Emotional Dictionary
    Huang, Shu-hui
    Yan, Xin
    Yu, Zheng-tao
    Liu, Xiao-hui
    Zhou, Feng
    [J]. PROCEEDINGS OF THE 2015 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT INFORMATION PROCESSING, 2015, 336 : 459 - 467
  • [23] Domain-specific ontology merging for the semantic web
    Taylor, JM
    Poliakov, D
    Mazlack, LJ
    [J]. NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society, 2005, : 418 - 423
  • [24] Ontology Driven Development of Domain-Specific Languages
    Ceh, Ines
    Crepinsek, Matej
    Kosar, Tomaz
    Mernik, Marjan
    [J]. COMPUTER SCIENCE AND INFORMATION SYSTEMS, 2011, 8 (02) : 317 - 342
  • [25] An automated domain-specific answer ontology construction
    Ko, Wei-Min
    Li, Huan-Chung
    [J]. NAFIPS 2007 - 2007 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, 2007, : 378 - +
  • [26] An Enhanced Approach to Map Domain-Specific Words in Cross-Domain Sentiment Analysis
    Geethapriya, A.
    Valli, S.
    [J]. INFORMATION SYSTEMS FRONTIERS, 2021, 23 (03) : 791 - 805
  • [27] An Enhanced Approach to Map Domain-Specific Words in Cross-Domain Sentiment Analysis
    A. Geethapriya
    S. Valli
    [J]. Information Systems Frontiers, 2021, 23 : 791 - 805
  • [28] Domain-specific requirements analysis framework: ontology-driven approach
    Banerjee S.
    Sarkar A.
    [J]. International Journal of Computers and Applications, 2019, 44 (01) : 23 - 47
  • [29] Automatic construction of domain-specific sentiment lexicon for unsupervised domain adaptation and sentiment classification
    Beigi, Omid Mohamad
    Moattar, Mohammad H.
    [J]. KNOWLEDGE-BASED SYSTEMS, 2021, 213
  • [30] Generating Version Convertors for Domain-Specific Languages
    de Geest, Gerardo
    Vermolen, Sander
    van Deursen, Arie
    Visser, Eelco
    [J]. FIFTEENTH WORKING CONFERENCE ON REVERSE ENGINEERING, PROCEEDINGS, 2008, : 197 - 201