Atjaunināt sīkdatņu piekrišanu

Web and Big Data: Third International Joint Conference, APWeb-WAIM 2019, Chengdu, China, August 13, 2019, Proceedings, Part II 2019 ed. [Mīkstie vāki]

Edited by , Edited by , Edited by , Edited by , Edited by , Edited by
  • Formāts: Paperback / softback, 431 pages, height x width: 235x155 mm, weight: 688 g, 115 Illustrations, color; 42 Illustrations, black and white; XIX, 431 p. 157 illus., 115 illus. in color., 1 Paperback / softback
  • Sērija : Information Systems and Applications, incl. Internet/Web, and HCI 11642
  • Izdošanas datums: 17-Jul-2019
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030260747
  • ISBN-13: 9783030260743
  • Mīkstie vāki
  • Cena: 68,33 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Standarta cena: 80,39 €
  • Ietaupiet 15%
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
  • Formāts: Paperback / softback, 431 pages, height x width: 235x155 mm, weight: 688 g, 115 Illustrations, color; 42 Illustrations, black and white; XIX, 431 p. 157 illus., 115 illus. in color., 1 Paperback / softback
  • Sērija : Information Systems and Applications, incl. Internet/Web, and HCI 11642
  • Izdošanas datums: 17-Jul-2019
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030260747
  • ISBN-13: 9783030260743

This two-volume set, LNCS 11641 and 11642, constitutes  the thoroughly refereed proceedings of the Third International Joint Conference, APWeb-WAIM 2019, held in Chengdu, China, in August 2019.  

The 42 full papers presented together with 17 short papers, and 6 demonstration papers were carefully reviewed and selected from 180 submissions.
The papers are organized around the following topics: Big Data Analytics; Data and Information Quality; Data Mining and Application; Graph Data and Social Networks; Information Extraction and Retrieval; Knowledge Graph; Machine Learning; Recommender Systems; Storage, Indexing and Physical Database Design; Spatial, Temporal and Multimedia Databases; Text Analysis and Mining; and Demo.

Big Data Analytics.- Data and Information Quality.- Data Mining and
Application.- Graph Data and Social Networks.- Information Extraction and
Retrieval.- Knowledge Graph.- Machine Learning.- Recommender Systems.-
Storage, Indexing and Physical Database Design.- Spatial, Temporal and
Multimedia Databases.- Text Analysis and Mining.