Parallel Recursive Deep Model for Sentiment Analysis

doi:10.1007/978-3-319-18032-8 2

	Parallel Recursive Deep Model for Sentiment Analysis
	Li, Changliang; Xu, Bo; Wu, Gaowei; He, Saike; Tian, Guanhua; Zhou, Yujun
	2015-05-19
会议名称	Analysis，the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2015)
会议录名称	Advances in Knowledge Discovery and Data Mining
会议日期	2015-5-19 ~ 2015-5-22
会议地点	Ho Chi Minh
摘要	Sentiment analysis has now become a popular research problem to tackle in Artificial Intelligence (AI) and Natural Language Processing (NLP) field. We introduce a novel Parallel Recursive Deep Model (PRDM) for predicting sentiment label distributions. The main trait of our model is to not only use the composition units, i.e., the vector of word, phrase and sentiment label with them, but also exploit the information encoded among the structure of sentiment label, by introducing a sentiment Recursive Neural Network (sentiment-RNN) together with RNTN. The two parallel neural networks together compose of our novel deep model structure, in which Sentiment-RNN and RNTN cooperate with each other. On predicting sentiment label distributions task, our model outperforms previous state of the art approaches on both full sentences level and phrases level by a large margin.
关键词	Sentiment Analysis Prdm Sentiment-rnn
DOI	10.1007/978-3-319-18032-8 2
URL	查看原文
收录类别	EI
语种	英语
引用统计
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/41144
专题	复杂系统认知与决策实验室_听觉模型与认知计算
通讯作者	Li, Changliang
推荐引用方式 GB/T 7714	Li, Changliang,Xu, Bo,Wu, Gaowei,et al. Parallel Recursive Deep Model for Sentiment Analysis[C],2015.