© 2015

Multimedia Data Mining and Analytics

Disruptive Innovation

  • Aaron K. Baughman
  • Jiang Gao
  • Jia-Yu Pan
  • Valery A. Petrushin

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Aaron K. Baughman, Jia-Yu Pan, Jiang Gao, Valery A. Petrushin
      Pages 3-28
  3. Mobile and Social Multimedia Data Exploration

    1. Front Matter
      Pages 29-29
    2. Jianbo Yuan, Quanzeng You, Jiebo Luo
      Pages 31-59
    3. Mario Cataldi, Luigi Di Caro, Claudio Schifanella
      Pages 61-91
    4. Ling-Yin Wei, Yu Zheng, Wen-Chih Peng
      Pages 93-116
    5. Yi Yu, Roger Zimmermann, Suhua Tang
      Pages 117-146
    6. Christel Amato, Marc Yvon, Wilfredo Ferré
      Pages 147-155
    7. Gerald Friedland, Adam Janin, Howard Lei, Jaeyoung Choi, Robin Sommer
      Pages 157-173
  4. Biometric Multimedia Data Processing

    1. Front Matter
      Pages 175-175
    2. Stefan van der Stockt, Aaron K. Baughman, Michael Perlitz
      Pages 177-204
    3. Aaron Lawson, Luciana Ferrer, Wen Wang, John Murray
      Pages 205-225
  5. Multimedia Data Modeling, Search and Evaluation

    1. Front Matter
      Pages 227-227
    2. Sadet Alcic, Stefan Conrad
      Pages 229-252
    3. Haoran Wang, Zhengzhong Zhou, Changcheng Xiao, Liqing Zhang
      Pages 253-267
    4. Kimiaki Shirahama, Kenji Kumabuchi, Marcin Grzegorzek, Kuniaki Uehara
      Pages 269-294
    5. Damianos Galanopoulos, Milan Dojchinovski, Krishna Chandramouli, Tomáš Kliegr, Vasileios Mezaris
      Pages 295-310
    6. Farhan Baluch, Laurent Itti
      Pages 311-326
    7. Qingzhong Liu, Andrew H. Sung, Zhongxue Chen, Lei Chen
      Pages 327-343

About this book


This authoritative text/reference provides fresh insights into the cutting edge of multimedia data mining, reflecting how the research focus has shifted towards networked social communities, mobile devices and sensors.

Presenting a detailed exploration into the progression of the field, the book describes how the history of multimedia data processing can be viewed as a sequence of disruptive innovations. Across the chapters, the discussion covers the practical frameworks, libraries, and open source software that enable the development of ground-breaking research into practical applications.

Topics and features:

·         Contains contributions from an international selection of pre-eminent authorities in the field

·         Reviews how disruptive innovations in mobile, social, cognitive, cloud and organic based computing impacts upon the development of multimedia data mining

·         Provides practical details on implementing the technology for solving real-world multimedia problems

·         Includes chapters devoted to privacy issues in multimedia social environments, and large-scale biometric data processing

·         Covers content and concept based multimedia search, and advanced algorithms for multimedia data representation, processing and visualization

The illuminating viewpoints presented in this comprehensive volume will be of great interest to researchers and graduate students involved in machine learning and pattern recognition, as well as to professional multimedia analysts and software developers.


Audio Recognition Computer Vision Disruptive Innovation Image Processing Machine Learning Multi-Modal Data Processing Multimedia Data Mining Natural Language Processing Signal Processing

Editors and affiliations

  • Aaron K. Baughman
    • 1
  • Jiang Gao
    • 2
  • Jia-Yu Pan
    • 3
  • Valery A. Petrushin
    • 4
  1. 1.IBM Corp.DurhamUSA
  2. 2.Nokia Inc.SunnyvaleUSA
  3. 3.Google Inc.Mountain ViewUSA
  4. 4.4i, Inc.CarlsbadUSA

About the editors

Aaron K. Baughman is a member of the Special Events Group at IBM (USA) for World Wide Sports. Previously, he was Technical Lead on a DeepQA Embed Research project that included an instance of the Jeopardy! Challenge.

Jiang (John) Gao is a Principal Scientist in the Advanced Development and Technology Group at Nokia USA, working on multimedia and mobile applications, data mining and computer vision.

Jia-Yu Pan is a software engineer at Google (USA), working on data mining and anomaly detection in big data.

Valery A. Petrushin is a Principal Scientist in the Research and Development Group at Opera Solutions (USA). His previous publications include the successful Springer title Multimedia Data Mining and Knowledge Discovery.

Bibliographic information

Industry Sectors
IT & Software


“Multimedia data mining and analytics: disruptive innovation highlights new applications in multimedia data mining, presenting fascinating techniques together with comprehensive cases in practice. … this book is valuable for the insight it provides related to the challenges faced by fast developing technologies, their current needs and future promise. It is a practical guide, a useful handbook for academies and industry practitioners who have interest in multimedia data analysis.” (Shanshan Qi, Information Technology & Tourism, Vol. 16, 2016)