Transactions on large-scale data- and knowledge-centered systems
著者
書誌事項
Transactions on large-scale data- and knowledge-centered systems
（Lecture notes in computer science, 5740,
Springer, c2009-
- 1
- 25
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注記
"Journal subline"--Cover
Includes bibliographical references and index
内容説明・目次
- 巻冊次
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1 ISBN 9783642037214
内容説明
Data management, knowledge discovery, and knowledge processing are core and hot topics in computer science. They are widely accepted as enabling technologies for modern enterprises, enhancing their performance and their decision making processes. Since the 1990s the Internet has been the outstanding driving force for application development in all domains. An increase in the demand for resource sharing (e. g. , computing resources, s- vices, metadata, data sources) across different sites connected through networks has led to an evolvement of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications prov- ing high scalability. Current decentralized systems still focus on data and knowledge as their main resource characterized by: heterogeneity of nodes, data, and knowledge autonomy of data and knowledge sources and services large-scale data volumes, high numbers of data sources, users, computing resources dynamicity of nodes These characteristics recognize: (i) limitations of methods and techniques developed for centralized systems (ii) requirements to extend or design new approaches and methods enhancing efficiency, dynamicity, and scalability (iii) development of large scale, experimental platforms and relevant benchmarks to evaluate and validate scaling Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and agent systems supporting 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.
目次
Modeling and Management of Information Supporting Functional Dimension of Collaborative Networks.- A Universal Metamodel and Its Dictionary.- Data Mining Using Graphics Processing Units.- Context-Aware Data and IT Services Collaboration in E-Business.- Facilitating Controlled Tests of Website Design Changes Using Aspect-Oriented Software Development and Software Product Lines.- Frontiers of Structured Business Process Modeling.- Information Systems for Federated Biobanks.- Exploring Trust, Security and Privacy in Digital Business.- Evolution of Query Optimization Methods.- Holonic Rationale and Bio-inspiration on Design of Complex Emergent and Evolvable Systems.- Self-Adaptation for Robustness and Cooperation in Holonic Multi-Agent Systems.- Context Oriented Information Integration.- Data Sharing in DHT Based P2P Systems.- Reverse k Nearest Neighbor and Reverse Farthest Neighbor Search on Spatial Networks.
- 巻冊次
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25 ISBN 9783662495339
内容説明
This, the 25th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five fully revised selected papers focusing on data and knowledge management systems. Topics covered include a framework consisting of two heuristics with slightly different characteristics to compute the action rating of data stores, a theoretical and experimental study of filter-based equijoins in a MapReduce environment, a constraint programming approach based on constraint reasoning to study the view selection and data placement problem given a limited amount of resources, a formalization and an approximate algorithm to tackle the problem of source selection and query decomposition in federations of SPARQL endpoints, and a matcher factory enabling the generation of a dedicated schema matcher for a given schema matching scenario.
目次
On Expedited Rating of Data Stores.- A Theoretical and
Experimental Comparison of Filter-Based Equijoins in MapReduce.- Constraint
Optimization Method for Large-Scale Distributed View Selection.- On the
Selection of SPARQL Endpoints to Efficiently Execute Federated SPARQL Queries.-
YAM: A Step Forward for Generating a Dedicated Schema Matcher.
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