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Titlebook: Web and Big Data; APWeb-WAIM 2017 Inte Shaoxu Song,Matthias Renz,Yang-Sae Moon Conference proceedings 2017 Springer International Publishin

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發(fā)表于 2025-3-21 18:37:43 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Web and Big Data
副標(biāo)題APWeb-WAIM 2017 Inte
編輯Shaoxu Song,Matthias Renz,Yang-Sae Moon
視頻videohttp://file.papertrans.cn/1022/1021660/1021660.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Web and Big Data; APWeb-WAIM 2017 Inte Shaoxu Song,Matthias Renz,Yang-Sae Moon Conference proceedings 2017 Springer International Publishin
描述.This book constitutes the thoroughly refereed post-conference proceedings of the First APWeb-WAIM 2017 Workshops, held jointly with the First International Joint Conference APWeb-WAIM 2017, held in Beijing, China, in July 2017. The 25 full papers presented were carefully reviewed and selected from 40 submissions. The papers originating from six workshops present cutting-edge ideas, ?results, experiences, techniques, and tools from all aspects of web data ?management with the focus on mobile web data analytics; big spatial data and urban computing; graph data management and analytics; mobility analytics from spatial and social data..
出版日期Conference proceedings 2017
關(guān)鍵詞spatiotemporal data; semi-structured data; mobile data; web data; big data; data management; data mining; d
版次1
doihttps://doi.org/10.1007/978-3-319-69781-9
isbn_softcover978-3-319-69780-2
isbn_ebook978-3-319-69781-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2017
The information of publication is updating

書目名稱Web and Big Data影響因子(影響力)




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https://doi.org/10.1007/978-3-319-69781-9spatiotemporal data; semi-structured data; mobile data; web data; big data; data management; data mining; d
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Web and Big Data978-3-319-69781-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
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An Adversarial Machine Learning Model Against Android Malware Evasion Attacks the security of the classifier. To effectively counter these evasion attacks, we then propose a robust secure-learning paradigm and show that it can improve system security against a wide class of evasion attacks. The proposed model can also be readily applied to other security tasks, such as anti-
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A Joint Model for Water Scarcity Evaluationty Index, and we creatively add population as the sixth key component. The prediction can be used as an important indicator for the government to take some specific intervention measures to help alleviate the severe water shortage and achieve sustainable development of water resources.
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