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Transactions on Large-Scale Data- and Knowledge-Centered Systems LVI: Special Issue on Data Management - Principles, Technologies, and Applications 2024 ed. [Mīkstie vāki]

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  • Formāts: Paperback / softback, 153 pages, height x width: 235x155 mm, 57 Illustrations, color; 7 Illustrations, black and white; IX, 153 p. 64 illus., 57 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14790
  • Izdošanas datums: 21-Jul-2024
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3662696029
  • ISBN-13: 9783662696026
  • Mīkstie vāki
  • Cena: 60,29 €*
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  • Formāts: Paperback / softback, 153 pages, height x width: 235x155 mm, 57 Illustrations, color; 7 Illustrations, black and white; IX, 153 p. 64 illus., 57 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14790
  • Izdošanas datums: 21-Jul-2024
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3662696029
  • ISBN-13: 9783662696026
The LNCS journal Transactions on Large-scale Data and Knowledge-centered Systemsfocuses 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 maindriving force behind application development in all domains. An increase in the demand forresource sharing across different sites connected through networks has led to an evolution ofdata- and knowledge-management systems from centralized systems to decentralized systemsenabling large-scale distributed applications providing high scalability.





This, the 56th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems,contains five fully revised and extended papers selected from the 39th conference on DataManagement - Principles, Technologies and Applications, BDA 2023. The topics cover awide range of timely data management research topics on adaptive learning, personal datamanagement systems, topic discovery in large corpora, spatio-temporal query processing, anddata generation.

Multi-Objective Test Recommendation for Adaptive Learning.- Handling Dropouts in Federating Learning with Personal Data Management Systems.- ANTM: Aligned Neural Topic Models for Exploring Evolving Topics.- A Data-Driven Model Selection Approach to Spatio-Temporal Prediction.- Optimistic Data Generation for JSON Schema.