Joint Learning with Keyword Extraction for Event Detection in Social Media
Guandan Chen; Wenji Mao; Qingchao Kong; Han Han
2018
Conference NameIEEE Intelligence and Security Informatics (ISI) 2018
Conference Date2018.11.8-2018.11.10
Conference PlaceMiami, FL, USA
AbstractEvent detection for social media is an important social media analytics task in security domain, which can provide valuable information for decision making, intelligence analysis and public management. Traditional event detection methods either rely on simple term frequency based features, or take the bag of words assumption. Recently, some deep neural network based event detection methods are proposed. However, these methods still have some drawbacks. Firstly, they do not provide an effective way to learn the connection between message representation and event representation, but simply use average of message representations as the event representation. Secondly, representations in the hidden space lack interpretability compared to the traditional event keyword representation. To deal with these weaknesses, we propose an event detection approach joint learning with keyword extraction. We provide an episode learning strategy to enable the training of event representation update. In addition, by joint learning with keyword extraction, the model is more explainable, and can achieve a better performance. As the selection of a set of keywords is a combinatorial problem and non-differential, we also employ reinforcement learning in our approach. Experiments on a public available dataset show the superiority of our approach compared with baseline methods.
KeywordEvent Detection Keyword Extraction Deep Learning
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21799
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
互联网大数据与安全信息
Affiliation1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China
2.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China
3.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China
4.CNCERT/CC, China
Recommended Citation
GB/T 7714
Guandan Chen,Wenji Mao,Qingchao Kong,et al. Joint Learning with Keyword Extraction for Event Detection in Social Media[C],2018.
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