Sentiment-Polarized Word Embedding for Multi-label Sentiment Classification

Sentiment analysis of text is an import branch of natural language process. In this paper, we propose a sentiment-polarized word embedding model (SPWE) with emotional dictionary, which is a variant of the C&W. Our model is able to represent and differentiate the emotional semantic of words, whic...

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Vydané v:	2018 IEEE 4th International Conference on Computer and Communications (ICCC) s. 2312 - 2316
Hlavní autori:	Zhang, Liujie, Zhou, Yanquan, Chen, Ruiqi, Duan, Xiuyu
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.12.2018
Predmet:	Dictionaries Feature extraction Linear programming multi-label Semantics Sentiment analysis sentiment classification sentiment-polarized Task analysis Training word embedding
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