Transactions on Large-Scale Data- and Knowledge-Centered Systems XLI -
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Présentation Transactions On Large - Scale Data - And Knowledge - Centered Systems Xli de Collectif Format Broché
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Résumé :
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,the 41st issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains seven revised, extended papers selected from the 4th International Conference on Future Data and Security Engineering, FDSE 2017, which was held in Ho Chi Minh City, Vietnam, in November/December 2017. The main focus of this special issue is on data and security engineering, as well as engineering applications.
Sommaire: Fast Distributed Top-Q and Top-K Query Processing.- Invariant Properties and Bounds on a Finite Time Consensus Algorithm.- Parallel Learning Algorithms of Local Support Vector Regression for Dealing with Large Datasets.- A Parallel Incremental Frequent Itemsets Mining IFIN+.- Improvement and Extensive Evaluation.- Automated Security Analysis of Authorization Policies with Contextual Information.- Classification Methods in Colon Disease Information System.- Application of Regularized Online Sequential Learning for Glucose Correction.
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