Transactions on Large-Scale Data- and Knowledge-Centered Systems XLIV, 1st ed. 2020
Special Issue on Data Management - Principles, Technologies, and Applications
Transactions on Large-Scale Data- and Knowledge-Centered Systems Series

Coordinators: Hameurlain Abdelkader, Tjoa A Min, Lamarre Philippe, Zeitouni Karine

Language: English

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195 p. · 15.5x23.5 cm · Paperback

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 (e.g., computing resources, services, metadata, data sources) 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.

This, the 44th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six fully revised and extended papers selected from the 35th conference on Data Management ? Principles, Technologies and Applications, BDA 2019. The topics covered include big data, graph data streams, workflow execution in the cloud, privacy in crowdsourcing, secure distributed computing, machine learning, and data mining for recommendation systems.


Scalable Saturation of Streaming RDF Triples.- Efficient Execution of Scientific Workflows in the Cloud through Adaptive Caching.- From Task Tuning to Task Assignment in Privacy-Preserving.- Secure Distributed Queries over Large Sets of Personal Home Boxes.- Evaluating Classification Feasibility Using Functional Dependencies.- Enabling Decision Support through Ranking and Summarization of Association Rules for TOTAL Customers.

Focuses on hot topics in the field of data management

Topics range from big data to secure distributed computing and data mining for recommendation systems

Contains revised and extended versions of papers presented at BDA 2019