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Mining opinion summarizations using convolutional neural networks in Chinese microblogging systems
文献类型：期刊论文
| 作者 | Li, Qiudan1 ; Jin, Zhipeng1,2; Wang, Can1,2; Zeng, Daniel Dajun1,2,3; Daniel Dajun Zeng
|
| 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 |
| 通讯作者 | Daniel Dajun Zeng |
| 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 |
| 语种 | 英语 |
| WOS记录号 | WOS:000380595900022 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12270]  |
| 专题 | 自动化研究所_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 |
| 通讯作者 | Daniel Dajun Zeng |
| 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 |
| 推荐引用方式 GB/T 7714 | Li, Qiudan,Jin, Zhipeng,Wang, Can,et al. Mining opinion summarizations using convolutional neural networks in Chinese microblogging systems[J]. KNOWLEDGE-BASED SYSTEMS,2016,107(1):289-300. |
| APA | Li, Qiudan,Jin, Zhipeng,Wang, Can,Zeng, Daniel Dajun,&Daniel Dajun Zeng.(2016).Mining opinion summarizations using convolutional neural networks in Chinese microblogging systems.KNOWLEDGE-BASED SYSTEMS,107(1),289-300. |
| MLA | Li, Qiudan,et al."Mining opinion summarizations using convolutional neural networks in Chinese microblogging systems".KNOWLEDGE-BASED SYSTEMS 107.1(2016):289-300. |
入库方式： OAI收割
来源：自动化研究所
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