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
  • [41] Domain-Specific Image Caption Generator with Semantic Ontology
    Han, Seung-Ho
    Choi, Ho-Jin
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2020), 2020, : 526 - 530
  • [42] TEMPPLET: A new method for domain-specific ontology design
    Dong, Y
    Li, MS
    [J]. ENGINEERING AND DEPLOYMENT OF COOPERATIVE INFORMATION SYSTEMS, PROCEEDINGS, 2002, 2480 : 90 - 103
  • [43] An ontology-based framework for domain-specific modeling
    Walter, Tobias
    Parreiras, Fernando Silva
    Staab, Steffen
    [J]. SOFTWARE AND SYSTEMS MODELING, 2014, 13 (01): : 83 - 108
  • [44] Domain-Specific Ontology Concept Extraction and Hierarchy Extension
    Zhao, Grace
    Zhang, Xiaowen
    [J]. PROCEEDINGS OF THE 2018 2ND INTERNATIONAL CONFERENCE ON NATURAL LANGUAGE PROCESSING AND INFORMATION RETRIEVAL (NLPIR 2018), 2018, : 60 - 64
  • [45] Development and Alignment of a Domain-Specific Ontology for Question Answering
    Ou, Shiyan
    Pekar, Viktor
    Orasan, Constantin
    Spurk, Christian
    Negri, Matteo
    [J]. SIXTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, LREC 2008, 2008, : 2221 - 2228
  • [46] Knowledge representation for video assisted by domain-specific ontology
    Song, Dan
    Cho, Miyoung
    Choi, Chang
    Shin, Juhyun
    Park, Jongan
    Kim, Pankoo
    [J]. ADVANCES IN KNOWLEDGE ACQUISITION AND MANAGEMENT, 2006, 4303 : 144 - +
  • [47] An ontology-based framework for domain-specific modeling
    Tobias Walter
    Fernando Silva Parreiras
    Steffen Staab
    [J]. Software & Systems Modeling, 2014, 13 : 83 - 108
  • [48] Learning Domain-specific Sentiment Lexicon with Supervised Sentiment-aware LDA
    Yang, Min
    Zhu, Dingju
    Mustafa, Rashed
    Chow, Kam-Pui
    [J]. 21ST EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2014), 2014, 263 : 927 - +
  • [49] Domain-specific formal ontology of archaeology and its application in knowledge acquisition and analysis
    Chun-Xia Zhang
    Cun-Gen Cao
    Fang Gu
    Jin-Xin Si
    [J]. Journal of Computer Science and Technology, 2004, 19 : 290 - 301
  • [50] An Approach for Domain-Specific Design Pattern Identification Based on Domain Ontology
    Gkantouna, Vassiliki
    Papaioannou, Vaios
    Tzimas, Giannis
    Sabic, Zlatan
    [J]. ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS (AIAI 2019), 2019, 560 : 125 - 137