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Machine Learning and Data Mining in Pattern Recognition

10th International Conference, MLDM 2014, St. Petersburg, Russia, July 21-24, 2014. Proceedings

  • Petra Perner

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8556)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 8556)

Table of contents

  1. Front Matter
  2. Classification and Learning

    1. Eran Shaham, David Sarne, Boaz Ben-Moshe
      Pages 1-15
    2. Fatimah Binta Abdullahi, Frans Coenen, Russell Martin
      Pages 58-72
    3. Kitsana Waiyamai, Thanapat Kangkachit, Bordin Saengthongloun, Thanawin Rakthanmanon
      Pages 78-90
    4. Nachai Limsetto, Kitsana Waiyamai
      Pages 91-106
    5. Alexander Kuleshov, Alexander Bernstein
      Pages 119-133
  3. Clustering

    1. Marwan Hassani, Pascal Spaus, Thomas Seidl
      Pages 134-148
    2. Maria Barouti, Daniel Keren, Jacob Kogan, Yaakov Malinovsky
      Pages 149-162
    3. Orestes G. Manzanilla-Salazar, Jesús Espinal-Kohler, Ubaldo M. García-Palomares
      Pages 163-174
  4. Outlier Detection

    1. Kliton Andrea, Georgy Shevlyakov, Natalia Vassilieva, Alexander Ulanov
      Pages 190-197
  5. Hierarchical Classification

    1. Esra’a Alshdaifat, Frans Coenen, Keith Dures
      Pages 198-212
    2. Thanawut Ananpiriyakul, Piyapan Poomsirivilai, Peerapon Vateekul
      Pages 213-227
  6. Time Series and Sequential Pattern Mining

  7. Signal, Image, and Video Mining

    1. Bernd Neumann, Lothar Hotz, Pascal Rost, Jos Lehmann
      Pages 285-299
    2. Aleksandr Larin, Oleg Seredin, Andrey Kopylov, Sy-Yen Kuo, Shih-Chia Huang, Bo-Hao Chen
      Pages 300-314
    3. Anton Malenichev, Valentina Sulimova, Olga Krasotkina, Vadim Mottl, Anatoly Markov
      Pages 315-327
    4. Luca Piras, Giorgio Giacinto
      Pages 328-342
  8. Medical Data Mining

    1. Elina Maliarsky, Mireille Avigal, Maya Herman
      Pages 343-360
    2. Andreia Silva, Cláudia Antunes
      Pages 361-375
  9. Social Media Mining

    1. Tuhin Sharma, Durga Toshniwal
      Pages 376-392
  10. Data Mining in Education

  11. Data Mining in Marketing

  12. Text and Document Mining

    1. Indu Mati Anand, Anurag Wakhlu, Pranav Anand
      Pages 431-436
    2. Ahmet Selman Bozkır, Ebru Akçapınar Sezer
      Pages 457-470
    3. Marijn Schraagen, Walter Kosters
      Pages 471-483
  13. Neural Networks

    1. Sebastian Otte, Marcus Liwicki, Dirk Krechel
      Pages 484-497
  14. Applications in Geography

    1. Luca Mazzola, Pedro Chahuara, Aris Tsois, Mauro Pedone
      Pages 498-512
  15. Software Engineering

    1. Jyotiska Nath Khasnabish, Mitali Sodhi, Jayati Deshmukh, G. Srinivasaraghavan
      Pages 513-522
  16. Aspects of Data Mining

  17. Back Matter

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

Keywords

association rule mining bayesian network bioinformatics crowdsourcing data mining ensemble method machine learning social network analysis support vector machines vizualisation

Editors and affiliations

  • Petra Perner
    • 1
  1. 1.Institute of Computer Vision and Applied Computer Sciences, IBaI,LeipzigGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-08979-9
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-08978-2
  • Online ISBN 978-3-319-08979-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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