Transactions on Large-Scale Data- and Knowledge-Centered Systems XLII, 1st ed. 2019
Transactions on Large-Scale Data- and Knowledge-Centered Systems Series

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 42nd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, consists of five revised selected regular papers, presenting the following topics: Privacy-Preserving Top-k Query Processing in Distributed Systems; Trust Factors and Insider Threats in Permissioned Distributed Ledgers: An Analytical Study and Evaluation of Popular DLT Frameworks; Polystore and Tensor Data Model for Logical Data Independence and Impedance Mismatch in Big Data Analytics; A General Framework for Multiple Choice Question Answering Based on Mutual Information and Reinforced Co-occurrence; Rejig: A Scalable Online Algorithm for Cache Server Configuration Changes. 

Privacy-Preserving Top-k Query Processing in Distributed Systems.- Trust Factors and Insider Threats in Permissioned Distributed Ledgers - An Analytical Study and Evaluation of Popular DLT Frameworks.- Polystore and Tensor Data Model for Logical Data Independence and Impedance Mismatch in Big Data Analytics.- A General Framework for Multiple Choice Question Answering Based on Mutual Information and Reinforced Co-occurrence.- Rejig: A Scalable Online Algorithm for Cache Server Configuration Changes.

Constitutes a regular issue of the Transactions on Large-Scale Data- and Knowledge-Centered Systems

Contains in-depth papers on topics ranging from privacy preserving to question answering based on mutual information and reinforced co-occurance

Presents a tensor data model for logical data independence and data impedance mismatch, as well as a scalable on-line algorithm that manages configuration changes while providing read-after-write consistency