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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXI [electronic resource] : Selected Papers from DaWaK 2012 / edited by Abdelkader Hameurlain, Josef Küng, Roland Wagner, Alfredo Cuzzocrea, Umeshwar Dayal.

Contributor(s): Hameurlain, Abdelkader [editor.] | Küng, Josef [editor.] | Wagner, Roland [editor.] | Cuzzocrea, Alfredo [editor.] | Dayal, Umeshwar [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Transactions on Large-Scale Data- and Knowledge-Centered Systems: 9260Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015Edition: 1st ed. 2015.Description: XIII, 185 p. 84 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662478042.Subject(s): Database management | Data mining | Artificial intelligence | Information storage and retrieval systems | Algorithms | Database Management | Data Mining and Knowledge Discovery | Artificial Intelligence | Information Storage and Retrieval | AlgorithmsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 005.74 Online resources: Click here to access online
Contents:
Efficient Level-Based Top-Down Data Cube Computation Using MapReduce -- Differentiated Multiple Aggregations in Multidimensional Databases -- MIRABEL DW: Managing Complex Energy Data in a Smart Grid -- Modular Neural Networks for Extending OLAP to Prediction -- Cut-and-Rewind: Extending Query Engine for Continuous Stream Analytics -- Mining Popular Patterns: A Novel Mining Problem and Its Application to Static Transactional Databases and Dynamic Data Streams -- Rare Pattern Mining from Data Streams Using SRP-Tree and Its Variants -- Improving Cross-Document Knowledge Discovery Through Content and Link Analysis of Wikipedia Knowledge.
In: Springer Nature eBookSummary: 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.
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Efficient Level-Based Top-Down Data Cube Computation Using MapReduce -- Differentiated Multiple Aggregations in Multidimensional Databases -- MIRABEL DW: Managing Complex Energy Data in a Smart Grid -- Modular Neural Networks for Extending OLAP to Prediction -- Cut-and-Rewind: Extending Query Engine for Continuous Stream Analytics -- Mining Popular Patterns: A Novel Mining Problem and Its Application to Static Transactional Databases and Dynamic Data Streams -- Rare Pattern Mining from Data Streams Using SRP-Tree and Its Variants -- Improving Cross-Document Knowledge Discovery Through Content and Link Analysis of Wikipedia Knowledge.

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.

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