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Big Data Analytics and Knowledge Discovery

19th International Conference, DaWaK 2017, Lyon, France, August 28–31, 2017, Proceedings

  • Ladjel Bellatreche
  • Sharma Chakravarthy
Conference proceedings DaWaK 2017

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10440)

Also part of the Information Systems and Applications, incl. Internet/Web, and HCI book sub series (LNISA, volume 10440)

Table of contents

  1. Front Matter
    Pages I-XIV
  2. New Generation Data Warehouses Design

  3. Cloud and NoSQL Databases

    1. Front Matter
      Pages 51-51
    2. Somayeh Sobati Moghadam, Jérôme Darmont, Gérald Gavin
      Pages 53-73
    3. Daniel Gaspar, Fabio Porto, Reza Akbarinia, Esther Pacitti
      Pages 74-87
    4. Fatma Abdelhedi, Amal Ait Brahim, Faten Atigui, Gilles Zurfluh
      Pages 88-102
  4. Advanced Programming Paradigms

    1. Front Matter
      Pages 103-103
    2. Elias Egho, Dominique Gay, Romain Trinquart, Marc Boullé, Nicolas Voisine, Fabrice Clérot
      Pages 105-119
    3. Alampally Anirudh, R. Uday Kiran, P. Krishna Reddy, M. Toyoda, Masaru Kitsuregawa
      Pages 120-129
    4. Peter Braun, Alfredo Cuzzocrea, Fan Jiang, Carson Kai-Sang Leung, Adam G. M. Pazdor
      Pages 130-145
  5. Non-functional Requirements Satisfaction

    1. Front Matter
      Pages 147-147
    2. Rundong Li, Ningfang Mi, Mirek Riedewald, Yizhou Sun, Yi Yao
      Pages 149-163
    3. Amir Khatibi, Fabio Porto, Joao Guilherme Rittmeyer, Eduardo Ogasawara, Patrick Valduriez, Dennis Shasha
      Pages 164-172
    4. Georgia Kougka, Anastasios Gounaris, Ulf Leser
      Pages 183-196
  6. Machine Learning

    1. Front Matter
      Pages 197-197
    2. Robespierre Pita, Everton Mendonça, Sandra Reis, Marcos Barreto, Spiros Denaxas
      Pages 214-227
    3. Joel Luís Carbonera
      Pages 228-243
    4. Sameendra Samarawickrama, Shanika Karunasekera, Aaron Harwood, Ramamohanarao Kotagiri
      Pages 244-258
    5. Arvind Kumar Shekar, Patricia Iglesias Sánchez, Emmanuel Müller
      Pages 259-273
    6. Zhun-Zheng Lin, Bi-Ru Dai
      Pages 286-299
  7. Social Media and Twitter Analysis

  8. Sentiment Analysis and User Influence

    1. Front Matter
      Pages 353-353
    2. Sandeep Sricharan Mukku, Subba Reddy Oota, Radhika Mamidi
      Pages 355-367
    3. Dorra Attiaoui, Arnaud Martin, Boutheina Ben Yaghlane
      Pages 368-382
    4. Sharanjit Kaur, Rakhi Saxena, Vasudha Bhatnagar
      Pages 383-390
    5. Nagendra Kumar, Yash Chandarana, Konjengbam Anand, Manish Singh
      Pages 391-406
  9. Knowledge Discovery

    1. Front Matter
      Pages 407-407
    2. Linfei Zhou, Wei Ye, Claudia Plant, Christian Böhm
      Pages 409-423
    3. Parfait Bemarisika, André Totohasina
      Pages 424-432
    4. Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao
      Pages 433-446
  10. Data Flow Management and Optimization

    1. Front Matter
      Pages 447-447
    2. Jim O’Donoghue, Mark Roantree, Andrew McCarren
      Pages 449-458
    3. Xiufeng Liu, Per Sieverts Nielsen
      Pages 459-470
  11. Back Matter
    Pages 487-488

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017.

The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in the following topical sections: new generation data warehouses design; cloud and NoSQL databases; advanced programming paradigms; non-functional requirements satisfaction; machine learning; social media and twitter analysis; sentiment analysis and user influence; knowledge discovery;  and data flow management and optimization.  

Keywords

data mining databases cloud computing artificial intelligence social networks map-reduce semantics learning systems world wide web distributed computer systems machine learning big data classification cluster analysis computational linguistics ontology distributed environments clustering algorithms Support Vector Machines (SVM) data security

Editors and affiliations

  • Ladjel Bellatreche
    • 1
  • Sharma Chakravarthy
    • 2
  1. 1.LIAS/ISAE-ENSMAChasseneuilFrance
  2. 2.University of Texas at ArlingtonArlingtonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-64283-3
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-64282-6
  • Online ISBN 978-3-319-64283-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site