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Machine Learning and Data Mining in Pattern Recognition

11th International Conference, MLDM 2015, Hamburg, Germany, July 20-21, 2015, Proceedings

  • Petra Perner

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9166)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 9166)

Table of contents

  1. Front Matter
    Pages I-IX
  2. Graph Mining

    1. Front Matter
      Pages 1-1
    2. Kaspar Riesen, Miquel Ferrer, Rolf Dornberger, Horst Bunke
      Pages 3-16
    3. Nimit Dhulekar, Srinivas Nambirajan, Basak Oztan, Bülent Yener
      Pages 32-52
  3. Classification and Regression

    1. Front Matter
      Pages 53-53
    2. Søren Atmakuri Davidsen, E. Sreedevi , M. Padmavathamma
      Pages 55-69
    3. Chao Tan, Jihong Guan, Shuigeng Zhou
      Pages 70-83
  4. Sentiment Analysis

    1. Front Matter
      Pages 85-85
    2. Gayane Shalunts, Gerhard Backfried
      Pages 87-97
    3. Angelo Corallo, Laura Fortunato, Marco Matera, Marco Alessi, Alessio Camillò, Valentina Chetta et al.
      Pages 98-112
  5. Data Preparation and Missing Values

    1. Front Matter
      Pages 113-113
    2. Tommi Kärkkäinen, Mirka Saarela
      Pages 140-154
  6. Association and Sequential Rule Mining

    1. Front Matter
      Pages 155-155
    2. Souleymane Zida, Philippe Fournier-Viger, Cheng-Wei Wu, Jerry Chun-Wei Lin, Vincent S. Tseng
      Pages 157-171
  7. Support Vector Machines

  8. Frequent Item Set Mining and Time Series Analysis

    1. Front Matter
      Pages 215-215
    2. Saber Salah, Reza Akbarinia, Florent Masseglia
      Pages 217-231
    3. Reza Akbarinia, Florent Masseglia
      Pages 232-247
  9. Clustering

    1. Front Matter
      Pages 249-249
    2. Aalaa Mojahed, Joao H. Bettencourt-Silva, Wenjia Wang, Beatriz de la Iglesia
      Pages 251-265
    3. Saullo Oliveira, Rosana Veroneze, Fernando J. Von Zuben
      Pages 266-280
    4. Kritsana Treechalong, Thanawin Rakthanmanon, Kitsana Waiyamai
      Pages 281-295
    5. Paul K. Amalaman, Christoph F. Eick
      Pages 296-310
  10. Text Mining

    1. Front Matter
      Pages 311-311
    2. Jagadeesh Patchala, Raj Bhatnagar, Sridharan Gopalakrishnan
      Pages 313-327
    3. D. Sejal, K. G. Shailesh, V. Tejaswi, Dinesh Anvekar, K. R. Venugopal, S. S. Iyengar et al.
      Pages 328-341
  11. Applications of Data Mining

    1. Front Matter
      Pages 355-355
    2. Nada Alzahrani, Rasha Alsulim, Nourah Alaseem, Ghada Badr
      Pages 357-367
    3. Elizabeth P. Chou
      Pages 395-402
    4. Mona Al-Saleem, Norah Al-Kathiry, Sara Al-Osimi, Ghada Badr
      Pages 403-414
    5. Guilherme Alberto Sousa Ribeiro, Alexandre Cesar Muniz de Oliveira, Antonio Luiz S. Ferreira, Shyam Visweswaran, Gregory F. Cooper
      Pages 415-424
  12. Data Mining in System Biology, Drug Discovery, and Medicine

  13. Back Matter
    Pages 453-454

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2015, held in Hamburg, Germany, in July 2015.

The 41 full papers presented were carefully reviewed and selected from 123 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 Biclustering Big data Bioinformatics Data cloud geometry Data mining Ensemble method Genetic algorithms Image mining Knowledge discovery in databases Machine learning Ontology Recommendation Robust statistics Semi-supervised learning Social network analysis Support vector machines Uncertainty Visualization

Editors and affiliations

  • Petra Perner
    • 1
  1. 1.IBaILeipzigGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-21024-7
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-21023-0
  • Online ISBN 978-3-319-21024-7
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site