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Titlebook: Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXII; Special Issue on Big Abdelkader Hameurlain,Josef Küng,Takahiro Hara

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書目名稱Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXII
副標(biāo)題Special Issue on Big
編輯Abdelkader Hameurlain,Josef Küng,Takahiro Hara
視頻videohttp://file.papertrans.cn/928/927980/927980.mp4
概述Topics range from information leakage detection to Twitter stream mining.Covers data warehousing and ETL flows.Time series classification and association rule classifiers are also addressed.Includes s
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXII; Special Issue on Big Abdelkader Hameurlain,Josef Küng,Takahiro Hara
描述.The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments..This volume, the 32nd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, focuses on Big Data Analytics and Knowledge Discovery, and contains extended and revised versions of five papers sele
出版日期Book 2017
關(guān)鍵詞time series classification; association rule classifier; Twitter stream mining; Information leakage det
版次1
doihttps://doi.org/10.1007/978-3-662-55608-5
isbn_softcover978-3-662-55607-8
isbn_ebook978-3-662-55608-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag GmbH Germany 2017
The information of publication is updating

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