Multimedia Data Mining and Knowledge Discovery

  • Valery A. Petrushin
  • Latifur Khan

Table of contents

  1. Front Matter
    Pages I-XV
  2. Introduction

    1. Front Matter
      Pages I-XV
    2. Nilesh Patel, Ishwar Sethi
      Pages 14-41
  3. Multimedia Data Exploration and Visualization

    1. Front Matter
      Pages I-XV
    2. Lei Wang, Latifur Khan
      Pages 41-57
    3. Jessica Lin, Michail Vlachos, Eamonn Keogh, Dimitrios Gunopulos
      Pages 58-79
    4. Stefan Brecheisen, Hans-Peter Kriegel, Peer Krőger, Martin Pfeifle, Matthias Schubert, Arthur Zimek
      Pages 94-115
    5. Chuanjun Li, Latifur Khan, Balakrishnan Prabhakaran
      Pages 116-137
  4. Multimedia Data Indexing and Retrieval

    1. Front Matter
      Pages I-XV
    2. Ruofei Zhang, Zhongfei (Mark) Zhang
      Pages 141-167
    3. Marinette Bouet, Marie-Aude Aufaure
      Pages 168-184
    4. Menno Israël, Egon L. van den Broek, Peter van der Putten, Marten J. den Uyl
      Pages 185-206
  5. Multimedia Data Modeling and Evaluation

    1. Front Matter
      Pages I-XV
    2. James M. Kang, Muhammad Aurangzeb Ahmad, Ankur Teredesai, Roger Gaborski
      Pages 209-233
    3. Min Chen, Shu-Ching Chen, Mei-Ling Shyu, Chengcui Zhang
      Pages 234-258
    4. K. Selçuk Candan, Jong Wook Kim, Huan Liu, Reshma Suvarna, Nitin Agarwal
      Pages 259-290
    5. Xin Li, William Grosky, Nilesh Patel, Farshad Fotouhi
      Pages 307-324
    6. Sergio A. Alvarez, Carolina Ruiz, Takeshi Kawato
      Pages 340-361
    7. Rafael Ramirez, Amaury Hazan, Esteban Maestre, Xavier Serra
      Pages 362-380
  6. Applications and Case Studies

    1. Front Matter
      Pages I-XV
    2. Simeon J. Simoff, Robert P. Biuk-Aghai
      Pages 383-403
    3. Kimiaki Shirahama, Koichi Ideno, Kuniaki Uehara
      Pages 404-426
    4. Gang Wei, Valery A. Petrushin, Anatole V. Gershman
      Pages 427-447
    5. Qin Ding, Charles Daniel
      Pages 448-457
    6. Sylvain Mongy, Fatma Bouali, Chabane Djeraba
      Pages 458-471
    7. Pavel Praks, Libor Machala, Václav Snášel
      Pages 472-486
  7. Back Matter
    Pages 509-521

About this book


Multimedia information is ubiquitous and essential in many applications, and repositories of multimedia are numerous and extremely large. Consequently, researchers and professionals need new techniques and tools for extracting the hidden, useful knowledge embedded within multimedia collections, thereby helping them discover relationships between the various elements and using this knowledge in decision-making applications.

Multimedia Data Mining and Knowledge Discovery, assembling the work of leading academic and professional/industrial researchers worldwide, provides an overview of the current state-of-the-art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research. Consisting of an introductory section and four topical parts, the book describes the objectives and current tendencies in multimedia data mining research and their applications. Each part contains an overview of its chapters and leads the reader with a structured approach through the diverse subjects in the field.

Topics and Features:

• Features a comprehensive introduction to multimedia data mining and its relevance today

• Presents a global perspective of the field and its various components

• Provides broad, yet thorough and detailed coverage of the subject

• Numerous chapters reference websites with supplementary materials and demonstrations

• Explores multimedia data exploration, multimedia data modeling and evaluation, and visualization

• Offers an entire part devoted to applications and case studies

Written with graduate students in mind, this much needed comprehensive survey of the current state of multimedia data mining and knowledge discovery will also serve as a valuable resource for researchers with interests in multimedia data mining, summarization, indexing, and retrieval.


Mapping Performance data analysis modeling multimedia reflection tools visualization

Editors and affiliations

  • Valery A. Petrushin
    • 1
  • Latifur Khan
    • 2
  1. 1.Accenture Technology LabsAccenture LtdChicagoUSA
  2. 2.School of Forest Resources and ConservationUniversity of FloridaRichardsonUSA

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