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This, the 37th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include data security in clouds, privacy languages, probabilistic modelling in linked data integration, business intelligence based on multi-agent systems, collaborative filtering, and prediction accuracy.
This volume, the 36th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains eight revised, extended papers selected from the 3rd International Conference on Future Data and Security Engineering, FDSE 2016, and the 10th International Conference on Advanced Computing and Applications, ACOMP 2016, which were held in Can Tho City, Vietnam, in November 2016. Topics covered include big data analytics, massive dataset mining, security and privacy, cryptography, access control, deep learning, crowd sourcing, database watermarking, and query processing and optimization.
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 46th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six fully revised selected regular papers. Topics covered include an elastic framework for genomic data management, medical data cloud federations, temporal pattern mining, scalable schema discovery, load shedding, and selectivity estimation using linked Bayesian networks.
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 22nd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six revised selected regular papers. Topics covered include algorithms for large-scale private analysis, modelling of entities from social and digital worlds and their relations, querying virtual security views of XML data, recommendation approaches using diversity-based clustering scores, hypothesis discovery, and data aggregation techniques in sensor netwo rk environments.
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 seventh issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers on the following topics: data management, data streams, service-oriented computing, abstract algebraic frameworks, RDF and ontologies, and conceptual model frameworks.
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. This, the 47th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, constitutes a special issue focusing on Digital Ecosystems and Social Networks. The 9 revised selected papers cover topics that include Social Big Data, Data Analysis, Cloud-Based Feedback, Experience Ecosystems, Pervasive Environments, and Smart Systems.
This volume, the 34th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, constitutes a special issue consisting of seven papers on the subject of Consistency and Inconsistency in Data-Centric Applications. The volume opens with an invited article on basic postulates for inconsistency measures. Three of the remaining six papers are revised, extended versions of papers presented at the First International Workshop on Consistency and Inconsistency, COIN 2016, held in conjunction with DEXA 2016 in Porto, Portugal, in September 2016. The other three papers were selected from submissions to a call for contributions to this edition. Each of the papers highlights a particular subtopic. However, all are concerned with logical inconsistencies that are either to be systematically avoided, or reasoned with consistently, i.e., without running the danger of an explosion of inferences.
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 21st issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, focuses on Data Warehousing and Knowledge Discovery from Big Data, and contains extended and revised versions of eight papers selected as the best papers from the 14th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2012), held in Vienna, Austria, during September 3-6, 2012. These papers cover several advanced Big Data topics, ranging from data cube computation using MapReduce to multiple aggregations over multidimensional databases, from data warehousing systems over complex energy data to OLAP-based prediction models, from extended query engines for continuous stream analytics to popular pattern mining, and from rare pattern mining to enhanced knowledge discovery from large cross-document corpora.
This book constitutes the refereed post-conference proceedings for the VLBD conference workshops entitled: Towards Polystores That Manage Multiple Databases, Privacy, Security and/or Policy Issues for Heterogenous Data (Poly 2019) and the Fifth International Workshop on Data Management and Analytics for Medicine and Healthcare (DMAH 2019), held in Los Angeles, CA, USA, in August 2019, in conjunction with the 45th International Conference on Very Large Data Bases, VLDB 2019. The 20 regular papers presented together with 2 keynote papers were carefully reviewed and selected from 31 initial submissions. The papers are organized in topical sections named: Poly 2019: Privacy, Security and/or Policy Issues for Heterogenous Data; Building Polystore Systems. DMAH 2019: Database Enabled Biomedical Research; AI for Healthcare; Knowledge Discovery from Unstructured Biomedical Data; Blockchain and Privacy Preserving Data Management.