A Fuzzy System for Concept-Level Sentiment Analysis

被引:28
|
作者
Dragoni, Mauro [1 ]
Tettamanzi, Andrea G. B. [2 ]
Pereira, Celia da Costa [2 ]
机构
[1] FBK IRST, Trento, Italy
[2] Univ Nice Sophia Antipolis, UMR 7271, I3S, Sophia Antipolis, France
来源
关键词
Fuzzy set theory - Data mining - Semantics;
D O I
10.1007/978-3-319-12024-9_2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An emerging field within Sentiment Analysis concerns the investigation about how sentiment concepts have to be adapted with respect to the different domains in which they are used. In the context of the Concept-Level Sentiment Analysis Challenge, we presented a system whose aims are twofold: (i) the implementation of a learning approach able to model fuzzy functions used for building the relationships graph representing the appropriateness between sentiment concepts and different domains (Task 1); and (ii) the development of a semantic resource based on the connection between an extended version of WordNet, SenticNet, and ConceptNet, that has been used both for extracting concepts (Task 2) and for classifying sentences within specific domains (Task 3).
引用
收藏
页码:21 / 27
页数:7
相关论文
共 50 条
  • [21] Concept-Level Sentiment Analysis with Dependency-Based Semantic Parsing: A Novel Approach
    Agarwal, Basant
    Poria, Soujanya
    Mittal, Namita
    Gelbukh, Alexander
    Hussain, Amir
    COGNITIVE COMPUTATION, 2015, 7 (04) : 487 - 499
  • [22] Concept-Level Sentiment Analysis with Dependency-Based Semantic Parsing: A Novel Approach
    Basant Agarwal
    Soujanya Poria
    Namita Mittal
    Alexander Gelbukh
    Amir Hussain
    Cognitive Computation, 2015, 7 : 487 - 499
  • [23] PoliTwi: Early detection of emerging political topics on twitter and the impact on concept-level sentiment analysis
    Rill, Sven
    Reinel, Dirk
    Scheidt, Jorg
    Zicari, Roberto V.
    KNOWLEDGE-BASED SYSTEMS, 2014, 69 : 24 - 33
  • [24] Dependency Tree-Based Rules for Concept-Level Aspect-Based Sentiment Analysis
    Poria, Soujanya
    Ofek, Nir
    Gelbukh, Alexander
    Hussain, Amir
    Rokach, Lior
    SEMANTIC WEB EVALUATION CHALLENGE, 2014, 475 : 41 - 47
  • [25] A concept-level approach to the analysis of online review helpfulness
    Qazi, Aika
    Syed, Karim Bux Shah
    Raj, Ram Gopal
    Cambria, Erik
    Tahir, Muhammad
    Alghazzawi, Daniyal
    COMPUTERS IN HUMAN BEHAVIOR, 2016, 58 : 75 - 81
  • [26] Polarity Detection of Online Reviews Using Sentiment Concepts: NCU IISR Team at ESWC-14 Challenge on Concept-Level Sentiment Analysis
    Chung, Jay Kuan-Chieh
    Wu, Chi-En
    Tsai, Richard Tzong-Han
    SEMANTIC WEB EVALUATION CHALLENGE, 2014, 475 : 53 - 58
  • [27] Concept-level Rules for Capturing Domain Knowledge
    Moitra, Abha
    Crapo, Andrew
    Palla, Ravi
    2018 IEEE 12TH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC), 2018, : 260 - 264
  • [28] Dependency-Based Semantic Parsing for Concept-Level Text Analysis
    Poria, Soujanya
    Agarwal, Basant
    Gelbukh, Alexander
    Hussain, Amir
    Howard, Newton
    COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, CICLING 2014, PT I, 2014, 8403 : 113 - 127
  • [29] Detecting Concept-level Emotion Cause in Microblogging
    Song, Shuangyong
    Meng, Yao
    WWW'15 COMPANION: PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB, 2015, : 119 - 120
  • [30] Concept-Level Design Analytics for Blended Courses
    Albo, Laia
    Barria-Pineda, Jordan
    Brusilovsky, Peter
    Hernandez-Leo, Davinia
    TRANSFORMING LEARNING WITH MEANINGFUL TECHNOLOGIES, EC-TEL 2019, 2019, 11722 : 541 - 554