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Table of contents

  1. Front Matter
    Pages I-XVI
  2. Challenges in Data Mining and Big Data

    1. Front Matter
      Pages 1-1
    2. Shi Cheng, Bin Liu, Yuhui Shi, Yaochu Jin, Bin Li
      Pages 3-14
    3. Maxim Bakaev, Tatiana Avdeenko
      Pages 15-23
  3. Data Mining Algorithms

    1. Front Matter
      Pages 25-25
    2. Fangyu Gai, Zhiqiang Li, Xinwen Jiang, Hongchen Guo
      Pages 27-37
    3. Salim A., Amjesh R., Vinod Chandra S.S.
      Pages 38-47
    4. Ratna Hidayati, Katsutoshi Kanamori, Ling Feng, Hayato Ohwada
      Pages 59-66
    5. Jorge Leonardo Puentes Morantes, Nancy Yurani Ortiz Guevara, José Ignacio Rodriguez Molano
      Pages 67-74
  4. Frequent Itemset Mining

    1. Front Matter
      Pages 75-75
    2. Hristo Kyurkchiev, Kalinka Kaloyanova
      Pages 77-85
  5. Spatial Data Mining

  6. Prediction

    1. Front Matter
      Pages 135-135
    2. Vijay Krishna Menon, Nithin Chekravarthi Vasireddy, Sai Aswin Jami, Viswa Teja Naveen Pedamallu, Varsha Sureshkumar, K. P. Soman
      Pages 137-146
    3. Viliam Lendel, Lucia Pancikova, Lukas Falat
      Pages 165-174
    4. Johannes Kretzschmar, Kai Gebhardt, Christoph Theiß, Volkmar Schau
      Pages 175-184
  7. Feature Selection

  8. Information Extraction

    1. Front Matter
      Pages 217-217
    2. Kevin Möhlmann, Jörn Syrbe
      Pages 219-226
    3. Tanisha Jhalani, Vibhor Kant, Pragya Dwivedi
      Pages 235-243
  9. Classification

    1. Front Matter
      Pages 245-245
    2. Fábbio Borges, Ivan Silva, Ricardo Fernandes, Lucas Moraes
      Pages 247-252
    3. Myeongsu Kang, Gopala Krishnan Ramaswami, Melinda Hodkiewicz, Edward Cripps, Jong-Myon Kim, Michael Pecht
      Pages 253-261
    4. Pei-Chann Chang, Jheng-Long Wu, Cheng-Chin Tsao, Chin-Yuan Fan
      Pages 262-269
    5. Jing Peng, Alex J. Aved
      Pages 270-275
  10. Anomaly Pattern and Diagnosis

    1. Front Matter
      Pages 277-277
    2. Ngo Duy Khanh Vy, Duong Tuan Anh
      Pages 279-287
    3. Alexandru G. Floares, George A. Calin, Florin B. Manolache
      Pages 288-295
    4. Marisa Esteves, Henrique Vicente, Sabino Gomes, António Abelha, M. Filipe Santos, José Machado et al.
      Pages 296-308
  11. Data Visualization Analysis

    1. Front Matter
      Pages 309-309
    2. Sarwar Jahan Morshed, Juwel Rana, Marcelo Milrad
      Pages 311-320
    3. Qiaolian Liu, Jianfei Zhao, Naiwang Guo, Ding Xiao, Chuan Shi
      Pages 321-329
    4. Dimitri N. Mavris, Michael Balchanos, WoongJe Sung, Olivia J. Pinon
      Pages 330-341
    5. Youcef Abdelsadek, Kamel Chelghoum, Francine Herrmann, Imed Kacem, Benoît Otjacques
      Pages 342-349
  12. Privacy Policy

    1. Front Matter
      Pages 351-351
    2. Sheak Rashed Haider Noori, Md. Kamrul Hossain, Juwel Rana
      Pages 353-363
    3. Lukasz Krzywiecki, Krzysztof Majcher, Wojciech Macyna
      Pages 364-372
    4. Amir Rezapour, Wei Wu, Hung-Min Sun
      Pages 373-378
  13. Social Media

    1. Front Matter
      Pages 379-379

About these proceedings

Introduction

The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016.
The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions. The theme of DMBD 2016 is "Serving Life with Data Science". Data mining refers to the activity of going through big data sets to look for relevant or pertinent information.
The papers are organized in 10 cohesive sections covering all major topics of the research and development of data mining and big data and one Workshop on Computational Aspects of Pattern Recognition and Computer Vision.

Keywords

big data cloud computing data visualization spatial data mining swarm intelligence

Editors and affiliations

  • Ying Tan
    • 1
  • Yuhui Shi
    • 2
  1. 1.Peking UniversityBeijingChina
  2. 2.Xi'an Jiaotong-Liverpool UniversitySuzhouChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-40973-3
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-40972-6
  • Online ISBN 978-3-319-40973-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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