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Transactions On Largescale Data And Knowledgecentered Systems Xxxiv Special Issue On Consistency And Inconsistency In Datacentric Applications 1st Edition Abdelkader Hameurlain

  • SKU: BELL-6792206
Transactions On Largescale Data And Knowledgecentered Systems Xxxiv Special Issue On Consistency And Inconsistency In Datacentric Applications 1st Edition Abdelkader Hameurlain
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Transactions On Largescale Data And Knowledgecentered Systems Xxxiv Special Issue On Consistency And Inconsistency In Datacentric Applications 1st Edition Abdelkader Hameurlain instant download after payment.

Publisher: Springer-Verlag
File Extension: PDF
File size: 6.75 MB
Pages: 194
Author: Abdelkader Hameurlain, Josef Küng, Roland Wagner, Hendrik Decker (eds.)
ISBN: 9783662559468, 9783662559475, 3662559463, 3662559471
Language: English
Year: 2017
Edition: 1

Product desciption

Transactions On Largescale Data And Knowledgecentered Systems Xxxiv Special Issue On Consistency And Inconsistency In Datacentric Applications 1st Edition Abdelkader Hameurlain by Abdelkader Hameurlain, Josef Küng, Roland Wagner, Hendrik Decker (eds.) 9783662559468, 9783662559475, 3662559463, 3662559471 instant download after payment.

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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