Joint Learning with Keyword Extraction for Event Detection in Social Media

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	Joint Learning with Keyword Extraction for Event Detection in Social Media
	Guandan Chen; Wenji Mao; Qingchao Kong; Han Han
	2018
会议名称	IEEE Intelligence and Security Informatics (ISI) 2018
会议日期	2018.11.8-2018.11.10
会议地点	Miami, FL, USA
摘要	Event 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.
关键词	Event Detection Keyword Extraction Deep Learning
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/21799
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
作者单位	1.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
推荐引用方式 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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