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Web Information Systems Engineering WISE 2016: 17th International Conference, Shanghai, China, November 8-10, 2016, Proceedings, Part I 1st ed. 2016 [Pehme köide]

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  • Formaat: Paperback / softback, 572 pages, kõrgus x laius: 235x155 mm, kaal: 8891 g, 173 Illustrations, black and white; XXIV, 572 p. 173 illus., 1 Paperback / softback
  • Sari: Information Systems and Applications, incl. Internet/Web, and HCI 10041
  • Ilmumisaeg: 02-Nov-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319487396
  • ISBN-13: 9783319487397
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Web Information Systems Engineering WISE 2016: 17th International Conference, Shanghai, China, November 8-10, 2016, Proceedings, Part I 1st ed. 2016Suurem pilt
  • Formaat: Paperback / softback, 572 pages, kõrgus x laius: 235x155 mm, kaal: 8891 g, 173 Illustrations, black and white; XXIV, 572 p. 173 illus., 1 Paperback / softback
  • Sari: Information Systems and Applications, incl. Internet/Web, and HCI 10041
  • Ilmumisaeg: 02-Nov-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319487396
  • ISBN-13: 9783319487397
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319487397.html
Märksõnad:
This two volume set LNCS 10041 and LNCS 10042 constitutes the proceedings of the 17th International Conference on Web Information Systems Engineering, WISE 2016, held in Shanghai, China, in November 2016.





The 39 full papers and 31 short papers presented in these proceedings were carefully reviewed and selected from 233 submissions. The papers cover a wide range of topics such as Social Network Data Analysis; Recommender Systems; Topic Modeling; Data Diversity; Data Similarity; Context-Aware Recommendation; Prediction; Big Data Processing; Cloud Computing; Event Detection; Data Mining; Sentiment Analysis; Ranking in Social Networks; Microblog Data Analysis; Query Processing; Spatial and Temporal Data; Graph Theory; Non-Traditional Environments; and Special Session on Data Quality and Trust in Big Data.

Social Network Data Analysis.- Recommender Systems.- Topic Modeling.- Data Diversity.- Data Similarity.- Context-Aware Recommendation.- Prediction.- Big Data Processing.- Cloud Computing.- Event Detection.- Data Mining.- Sentiment Analysis.- Ranking in Social Networks.- Microblog Data Analysis.- Query Processing.- Spatial and Temporal Data.- Graph Theory.- Non-Traditional Environments.- and Special Session on Data Quality and Trust in Big Data.