Parallel Recursive Deep Model for Sentiment Analysis
Li, Changliang1; Xu, Bo1; Wu, Gaowei1; He, Saike1; Tian, Guanhua1; Zhou, Yujun2
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
DOI10.1007/978-3-319-18032-8 2
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收录类别EI
语种英语
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文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/10778
专题数字内容技术与服务研究中心_听觉模型与认知计算
通讯作者Li, Changliang
作者单位1.Institute of Automation Chinese Academy of Sciences
2.Jiangsu Jinling Science and Technology Group Co., Ltd
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.
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