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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXI - Selected Papers from DaWaK 2012 (Paperback, 1st ed. 2015)
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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXI - Selected Papers from DaWaK 2012 (Paperback, 1st ed. 2015)
Series: Lecture Notes in Computer Science, 9260
Expected to ship within 10 - 15 working days
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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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