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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXII - Special Issue on Big Data Analytics and Knowledge Discovery (Paperback, 1st ed. 2017)
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Discovery Miles 15 390
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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXII - Special Issue on Big Data Analytics and Knowledge Discovery (Paperback, 1st ed. 2017)
Series: Transactions on Large-Scale Data- and Knowledge-Centered Systems, 10420
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 32nd issue of Transactions on
Large-Scale Data- and Knowledge-Centered Systems, focuses on Big
Data Analytics and Knowledge Discovery, and contains extended and
revised versions of five papers selected from the 17th
International Conference on Big Data Analytics and Knowledge
Discovery, DaWaK 2015, held in Valencia, Spain, during September
1-4, 2015. The five papers focus on the exact detection of
information leakage, the binary shapelet transform for multiclass
time series classification, a discrimination-aware association rule
classifier for decision support (DAAR), new word detection and
tagging on Chinese Twitter, and on-demand snapshot maintenance in
data warehouses using incremental ETL pipelines, respectively.
discovery,="" contains="" extended="" revised="" versions=""
five="" papers="" selected="" from="" 17th="" international=""
conference="" discovery="" (dawak="" 2015),="" held="" in=""
valencia,="" spain,="" during="" september="" 1-4,="" 2015.=""
focus="" exact="" detection="" information="" leakage,="" binary=""
shapelet="" transform="" for="" multiclass="" time="" series=""
classification,="" a="" discrimination-aware="" association=""
rule="" classifier="" decision="" support="" (daar),="" new=""
word="" tagging="" chinese="" twitter,="" on-demand="" snapshot=""
maintenance="" warehouses="" using="" incremental="" etl=""
pipelines,="" respectively.
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