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Titlebook: Intelligence and Security Informatics; Pacific Asia Worksho G. Alan Wang,Xiaolong Zheng,Hsinchun Chen Conference proceedings 2013 Springer-

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書目名稱Intelligence and Security Informatics
副標(biāo)題Pacific Asia Worksho
編輯G. Alan Wang,Xiaolong Zheng,Hsinchun Chen
視頻videohttp://file.papertrans.cn/470/469297/469297.mp4
概述Up-to-date results.Fast-track conference proceedings.State-of-the-art research
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Intelligence and Security Informatics; Pacific Asia Worksho G. Alan Wang,Xiaolong Zheng,Hsinchun Chen Conference proceedings 2013 Springer-
描述This book constitutes the refereed proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2013, held in Beijing, China, in August 2013 in conjunction with the International Joint Conference on Artificial Intelligence (IJCAI 2013). The 4 revised full papers presented together with 7 short papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on information sharing and data/text mining; terrorism informatics; network-based data analytics; and information access and security.
出版日期Conference proceedings 2013
關(guān)鍵詞attack prevention; computer networks; machine learning; social networks; social web
版次1
doihttps://doi.org/10.1007/978-3-642-39693-9
isbn_softcover978-3-642-39692-2
isbn_ebook978-3-642-39693-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2013
The information of publication is updating

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Collective Intelligence for Suicide Surveillance in Web Forumsn the two parties is not well facilitated. In light of this situation, we present a system using collective intelligence from Internet users to efficiently and effectively identify suicidal people in order to provide timely intervention and promote better public health. We describe the system archit
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Identifying Peer Influence in Online Social Networks Using Transfer Entropyrmation. Identifying social influence in these newly emerging platforms can provide us with significant insights to better understand the interaction behaviors among online users. However, it is difficult for us to measure the influence quantitatively among user peers, since many key factors such as
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