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.

Role-Based Access Classification: Evaluating the Performance of Machine Learning Algorithms.- Top-k Queries over Distributed Uncertain Categorical Data.- On Knowledge Transfer from Cost-Based Optimization of Data-Centric Workflows to Business Process Redesign.- A New Knowledge Capitalization Framework in the Big Data Context through Shared Parameters Experiences.- DiNer - On Building Multilingual Disease-News Profiler.

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 43rd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include classification tasks, machine learning algorithms, top-k queries, business process redesign and a knowledge capitalization framework.

Contains detailed papers on topics ranging from machine-learning algorithms to the construction of a multilingual disease-news profiler Discusses the use of data in optimizing business processes Considers a knowledge capitalization framework in the Big Data context