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Advances in Big Data

Proceedings of the 2nd INNS Conference on Big Data, October 23-25, 2016, Thessaloniki, Greece

  • Plamen Angelov
  • Yannis Manolopoulos
  • Lazaros Iliadis
  • Asim Roy
  • Marley Vellasco

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 529)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Spyros E. Polykalas, George N. Prezerakos
    Pages 1-7
  3. Nikolaos Passalis, Anastasios Tefas
    Pages 8-17
  4. Ioannis Mademlis, Anastasios Tefas, Nikos Nikolaidis, Ioannis Pitas
    Pages 18-28
  5. Ilias Gialampoukidis, Stefanos Vrochidis, Ioannis Kompatsiaris
    Pages 29-38
  6. Jorge Luis Rivero Pérez, Bernardete Ribeiro
    Pages 39-49
  7. Hmida Hmida, Sana Ben Hamida, Amel Borgi, Marta Rukoz
    Pages 50-60
  8. Danai Triantafyllidou, Anastasios Tefas
    Pages 61-70
  9. Morten Gill Wollsen, John Hallam, Bo Nørregaard Jørgensen
    Pages 71-80
  10. Yoshitsugu Kakemoto, Shinichi Nakasuka
    Pages 89-99
  11. Giada Tacconelli, Manuel Roveri
    Pages 100-110
  12. Marios Bakratsas, Pavlos Basaras, Dimitrios Katsaros, Leandros Tassiulas
    Pages 111-119
  13. Cesare Alippi, Stavros Ntalampiras, Manuel Roveri
    Pages 120-130
  14. Talha Oktay, Ahmet Sayar
    Pages 131-138
  15. Luca Oneto, Emanuele Fumeo, Giorgio Clerico, Renzo Canepa, Federico Papa, Carlo Dambra et al.
    Pages 139-150
  16. Konstantina Karponi, Grigorios Tsoumakas
    Pages 151-159
  17. Shaona Ghosh, Adam Prügel-Bennett
    Pages 160-168
  18. Boris Lorbeer, Ana Kosareva, Bersant Deva, Dženan Softić, Peter Ruppel, Axel Küpper
    Pages 169-178
  19. Burak Köse, Süleyman Eken, Ahmet Sayar
    Pages 179-185
  20. Athena Vakali, Nikolaos Kitmeridis, Maria Panourgia
    Pages 186-194
  21. Cihan Küçükkeçeci, Adnan Yazıcı
    Pages 205-215
  22. Cesare Alippi, Giacomo Boracchi, Diego Carrera
    Pages 216-225
  23. Panagiotis Petridis, Anastasios Gounaris, Jordi Torres
    Pages 226-237
  24. Xiaowei Gu, Plamen P. Angelov, German Gutierrez, Jose Antonio Iglesias, Araceli Sanchis
    Pages 238-253
  25. Oscar Samudio, Marley Vellasco, Ricardo Tanscheit, Adriano Koshiyama
    Pages 262-272
  26. M. Vafopoulos, I. Anagnostopoulos, D. Negkas, G. Razis, G. Vafeiadis, I. Skaros et al.
    Pages 273-282
  27. Jingliang Chen, Dmytro Dosyn, Vasyl Lytvyn, Anatoliy Sachenko
    Pages 283-292
  28. Aikaterini K. Kalou, Dimitrios A. Koutsomitropoulos
    Pages 293-303
  29. Stamatios Giannoulakis, Nicolas Tsapatsoulis
    Pages 304-313
  30. Howard J. Parkinson, Gary J. Bamford
    Pages 314-322
  31. Asma Al-Drees, Reem Bin-Hezam, Ruba Al-Muwayshir, Wafa’ Haddoush
    Pages 323-332
  32. Back Matter
    Pages 347-348

About these proceedings

Introduction

The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.


Keywords

ANNS Autonomous, Online, Incremental Learning In Big Data Big Data Analytics Big Data And Cloud Computing Big Data Streams Analytics Cognitive Modeling And Big Data Deep Neural Network Learning Deep Reinforcement Learning Evolutionary Systems And Big Data Evolving Systems For Big Data Analytics Fuzzy Data Analysis Information Propagation Analysis INNS-BigData 2016 Learning Algorithms Streaming Data Neuromorphic Hardware Online Learning Online Social Networks Recommendation Systems/Collaborative Filtering For Big Data Systems Neuroscience Scalable Algorithms For Big Data

Editors and affiliations

  • Plamen Angelov
    • 1
  • Yannis Manolopoulos
    • 2
  • Lazaros Iliadis
    • 3
  • Asim Roy
    • 4
  • Marley Vellasco
    • 5
  1. 1.School of Computing and CommunicationsLancaster University LancasterUnited Kingdom
  2. 2.Data Engineering Lab, Dept. of InformaticsAristotle University of Thessaloniki ThessalonikiGreece
  3. 3.Lab of Forest Informatics (FiLAB)Democritus University of Thrace OrestiadaGreece
  4. 4.WPC Information Systems FacultyArizona State University TempeUSA
  5. 5.Electrical Engineering Dept, (ICA)Pontifical Catholic Univ of Rio de Janei Rio de JaneiroBrazil

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-47898-2
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-47897-5
  • Online ISBN 978-3-319-47898-2
  • Series Print ISSN 2194-5357
  • Series Online ISSN 2194-5365
  • Buy this book on publisher's site
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