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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXIV: Special Issue on Consistency and Inconsistency in Data-Centric Applications de Abdelkader Hameurlain

Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXIV: Special Issue on Consistency and Inconsistency in Data-Centric Applications: Lecture Notes in Computer Science, cartea 10620

Editat de Abdelkader Hameurlain, Josef Küng, Roland Wagner, Hendrik Decker
en Limba Engleză Paperback – 17 oct 2017
This volume, the 34th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, constitutes a special issue consisting of seven papers on the subject of Consistency and Inconsistency in Data-Centric Applications. The volume opens with an invited article on basic postulates for inconsistency measures. Three of the remaining six papers are revised, extended versions of papers presented at the First International Workshop on Consistency and Inconsistency, COIN 2016, held in conjunction with DEXA 2016 in Porto, Portugal, in September 2016. The other three papers were selected from submissions to a call for contributions to this edition. Each of the papers highlights a particular subtopic. However, all are concerned with logical inconsistencies that are either to be systematically avoided, or reasoned with consistently, i.e., without running the danger of an explosion of inferences.
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Specificații

ISBN-13: 9783662559468
ISBN-10: 3662559463
Pagini: 185
Ilustrații: IX, 185 p. 34 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.28 kg
Ediția:1st ed. 2017
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Transactions on Large-Scale Data- and Knowledge-Centered Systems

Locul publicării:Berlin, Heidelberg, Germany

Cuprins

Basic Postulates for Inconsistency Measures.- Batch Composite Transactions in Stream Processing.- Enhancing User Rating Database Consistency through Pruning.- A Second Generation of Peer-to-Peer Semantic Wikis.- Formalizing a Paraconsistent Logic in the Isabelle Proof Assistant.- A Proximity-Based Understanding of Conditionals.- Inconsistency-Tolerant Database Repairs and Simplified Repair Checking by Measure-Based Integrity Checking.

Textul de pe ultima copertă

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, the34th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, constitutes a special issue consisting of seven papers on the subject of Consistency and Inconsistency in Data-Centric Applications. The volume opens with an invited article on basic postulates for inconsistency measures. Three of the remaining six papers are revised, extended versions of papers presented at the First International Workshop on Consistency and Inconsistency, COIN 2016, held in conjunction with DEXA 2016 in Porto, Portugal, in September 2016. The other three papers were selected from submissions to a call for contributions to this edition. Each of the papers highlights a particular subtopic. However, all are concerned with logical inconsistencies that are either to be systematically avoided, or reasoned with consistently, i.e., without running the danger of an explosion of inferences.

Caracteristici

Focuses on consistency and inconsistency in data-centric applications Addresses logical inconsistencies and their avoidance or management Includes an invited paper on basic postulates for inconsistency measures Includes supplementary material: sn.pub/extras