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题名: Mining opinion summarizations using convolutional neural networks in Chinese microblogging systems
作者: Li Qiudan(李秋丹)1; Jin, Zhipeng1, 2; Wang, Can1, 2; Zeng Dajun(曾大军)1, 2, 3
刊名: KNOWLEDGE-BASED SYSTEMS
出版日期: 2016-09-01
卷号: 107, 期号:1, 页码:289-300
关键词: Chinese microblogging systems ; Hot topics ; Convolutional neural network ; Opinion summarization ; Maximal marginal relevance
DOI: 10.1016/j.knosys.2016.06.017
通讯作者: Daniel Dajun Zeng
文章类型: Article
英文摘要: Chinese microblogging is an increasingly popular social media platform. Accurately summarizing representative opinions from microblogs can increase understanding of the semantics of opinions. The unique challenges of Chinese opinion summarization in microblogging systems are automatic learning of important features and selection of representative sentences. Deep-learning methods can automatically discover multiple levels of representations from raw data instead of requiring manual engineering. However, there have been very few systematic studies on sentiment analysis of Chinese hot topics using deep-learning methods. Based on the latest deep-learning research, in this paper, we propose a convolutional neural network (CNN)-based opinion summarization method for Chinese microblogging systems. The model first applies CNN to automatically mine useful features and perform sentiment analysis; then, by making good use of the obtained sentiment features, the semantic relationships among features are computed according to a hybrid ranking function; and finally, representative opinion sentences that are semantically related to the features are extracted using Maximal Marginal Relevance, which meets "relevant novelty" requirements. Experimental results on two real-world datasets verify the efficacy of the proposed model. (C) 2016 Elsevier B.V. All rights reserved.
WOS标题词: Science & Technology ; Technology
类目[WOS]: Computer Science, Artificial Intelligence
研究领域[WOS]: Computer Science
关键词[WOS]: SENTIMENT ANALYSIS
收录类别: SCI
项目资助者: National Natural Science Foundation of China(91224008 ; Important National Science & Technology Specific Project(2013ZX10004218) ; 61172106 ; 61402123 ; 71402177)
语种: 英语
WOS记录号: WOS:000380595900022
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.ia.ac.cn/handle/173211/12270
Appears in Collections:复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心_期刊论文

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作者单位: 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA

Recommended Citation:
Qiudan Li,Zhipeng Jin,Can Wang,et al. Mining opinion summarizations using convolutional neural networks in Chinese microblogging systems[J]. Knowledge-Based Systems,2016,107(1):289–300.
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