Transactions on Large-Scale Data- and Knowledge-Centered Systems XXII: Lecture Notes in Computer Science, cartea 9430
Editat de Abdelkader Hameurlain, Josef Küng, Roland Wagneren Limba Engleză Paperback – 16 noi 2015
This, the 22nd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six revised selected regular papers. Topics covered include algorithms for large-scale private analysis, modelling of entities from social and digital worlds and their relations, querying virtual security views of XML data, recommendation approaches using diversity-based clustering scores, hypothesis discovery, and data aggregation techniques in sensor netwo
rk environments.
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Specificații
ISBN-13: 9783662485668
ISBN-10: 3662485664
Pagini: 183
Ilustrații: VII, 185 p. 56 illus. in color.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.28 kg
Ediția:1st ed. 2015
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
ISBN-10: 3662485664
Pagini: 183
Ilustrații: VII, 185 p. 56 illus. in color.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.28 kg
Ediția:1st ed. 2015
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
Public țintă
ResearchCuprins
BPMiner: Algorithms for Large-scale Private Analysis.- System Modeling and Trust Evaluation of Distributed Systems.- Efficient Querying of XML Data through Arbitrary Security Views.- Increasing Coverage in Distributed Search and Recommendation with Profile Diversity.- Hypothesis Discovery Exploiting Closed Chains of Relations.- An Analysis of Variance-Based Methods for Data Aggregation in Periodic Sensor Networks.
Caracteristici
Covers a wide range of hot topics in the field of data- and knowledge-management systems Topics covered include algorithms for large-scale private analysis, and modeling of entities from social and digital worlds and their relations Features recommendation approaches using diversity-based clustering scores, hypothesis discovery, and data aggregation techniques in sensor network environments Includes supplementary material: sn.pub/extras