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
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