SenticNet 3: A Common and Common-Sense Knowledge Base for Cognition-Driven Sentiment Analysis

被引:0
|
作者
Cambria, Erik [1 ]
Olsher, Daniel [2 ]
Rajagopal, Dheeraj [3 ]
机构
[1] Nanyang Technol Univ, Sch Comp Engn, Singapore, Singapore
[2] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
[3] Natl Univ Singapore, Temasek Labs, Singapore, Singapore
关键词
OPINIONS; MODEL;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
SenticNet is a publicly available semantic and affective resource for concept-level sentiment analysis. Rather than using graph-mining and dimensionality-reduction techniques, SenticNet 3 makes use of 'energy flows' to connect various parts of extended common and common-sense knowledge representations to one another. SenticNet 3 models nuanced semantics and sentics (that is, the conceptual and affective information associated with multi-word natural language expressions), representing information with a symbolic opacity of an intermediate nature between that of neural networks and typical symbolic systems.
引用
收藏
页码:1515 / 1521
页数:7
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