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Transactions on large-scale data- and knowledge-centered systems XXXVIII = special issue on database- and expert-systems applications /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Transactions on large-scale data- and knowledge-centered systems XXXVIII/ edited by Abdelkader Hameurlain ... [et al.].
Reminder of title:
special issue on database- and expert-systems applications /
remainder title:
Transactions on large-scale data- and knowledge-centered systems 38
other author:
Hameurlain, Abdelkader.
Published:
Berlin, Heidelberg :Springer Berlin Heidelberg : : 2018.,
Description:
xi, 173 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Computer networks - Congresses. - Security measures -
Online resource:
https://doi.org/10.1007/978-3-662-58384-5
ISBN:
9783662583845
Transactions on large-scale data- and knowledge-centered systems XXXVIII = special issue on database- and expert-systems applications /
Transactions on large-scale data- and knowledge-centered systems XXXVIII
special issue on database- and expert-systems applications /[electronic resource] :Transactions on large-scale data- and knowledge-centered systems 38edited by Abdelkader Hameurlain ... [et al.]. - Berlin, Heidelberg :Springer Berlin Heidelberg :2018. - xi, 173 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,112500302-9743 ;. - Lecture notes in computer science ;6140..
Bound-and-Filter Framework for Aggregate Reverse Rank Queries -- Syntactic Anonymisation of Shared Datasets in Resource Constrained Environments -- Towards Faster Similarity Search by Dynamic Reordering of Streamed Queries -- SjClust: A Framework for Incorporating Clustering into Set Similarity Join Algorithms -- A Query Processing Framework for Large-Scale Scientific Data Analysis -- Discovering Periodic-Correlated Patterns in Temporal Databases.
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 38th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of six papers selected from the 68 contributions presented at the 27th International Conference on Database and Expert Systems Applications, DEXA 2016, held in Porto, Portugal, in September 2016. Topics covered include query personalization in databases, data anonymization, similarity search, computational methods for entity resolution, array-based computations in big data analysis, and pattern mining.
ISBN: 9783662583845
Standard No.: 10.1007/978-3-662-58384-5doiSubjects--Topical Terms:
574534
Computer networks
--Security measures--Congresses.
LC Class. No.: QA76.9.A25
Dewey Class. No.: 005.8
Transactions on large-scale data- and knowledge-centered systems XXXVIII = special issue on database- and expert-systems applications /
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Bound-and-Filter Framework for Aggregate Reverse Rank Queries -- Syntactic Anonymisation of Shared Datasets in Resource Constrained Environments -- Towards Faster Similarity Search by Dynamic Reordering of Streamed Queries -- SjClust: A Framework for Incorporating Clustering into Set Similarity Join Algorithms -- A Query Processing Framework for Large-Scale Scientific Data Analysis -- Discovering Periodic-Correlated Patterns in Temporal Databases.
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