Music Data Mining

Music Data Mining

by Tao Li, Mitsunori Ogihara, George Tzanetakis
Released July 2011
Publisher(s): CRC Press
ISBN: 9781439835555

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Book description

The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to

Table of contents

  1. Front Cover
  2. Contents (1/2)
  3. Contents (2/2)
  4. List of Figures
  5. List of Tables
  6. Preface
  7. List of Contributors
  8. I. Fundamental Topics
    1. 1. Music Data Mining: An Introduction (1/8)
    2. 1. Music Data Mining: An Introduction (2/8)
    3. 1. Music Data Mining: An Introduction (3/8)
    4. 1. Music Data Mining: An Introduction (4/8)
    5. 1. Music Data Mining: An Introduction (5/8)
    6. 1. Music Data Mining: An Introduction (6/8)
    7. 1. Music Data Mining: An Introduction (7/8)
    8. 1. Music Data Mining: An Introduction (8/8)
    9. 2. Audio Feature Extraction (1/7)
    10. 2. Audio Feature Extraction (2/7)
    11. 2. Audio Feature Extraction (3/7)
    12. 2. Audio Feature Extraction (4/7)
    13. 2. Audio Feature Extraction (5/7)
    14. 2. Audio Feature Extraction (6/7)
    15. 2. Audio Feature Extraction (7/7)
  9. II. Classification
    1. 3. Auditory Sparse Coding (1/4)
    2. 3. Auditory Sparse Coding (2/4)
    3. 3. Auditory Sparse Coding (3/4)
    4. 3. Auditory Sparse Coding (4/4)
    5. 4. Instrument Recognition (1/8)
    6. 4. Instrument Recognition (2/8)
    7. 4. Instrument Recognition (3/8)
    8. 4. Instrument Recognition (4/8)
    9. 4. Instrument Recognition (5/8)
    10. 4. Instrument Recognition (6/8)
    11. 4. Instrument Recognition (7/8)
    12. 4. Instrument Recognition (8/8)
    13. 5. Mood and Emotional Classification (1/7)
    14. 5. Mood and Emotional Classification (2/7)
    15. 5. Mood and Emotional Classification (3/7)
    16. 5. Mood and Emotional Classification (4/7)
    17. 5. Mood and Emotional Classification (5/7)
    18. 5. Mood and Emotional Classification (6/7)
    19. 5. Mood and Emotional Classification (7/7)
    20. 6. Zipf's Law, Power Laws, and Music Aesthetics (1/10)
    21. 6. Zipf's Law, Power Laws, and Music Aesthetics (2/10)
    22. 6. Zipf's Law, Power Laws, and Music Aesthetics (3/10)
    23. 6. Zipf's Law, Power Laws, and Music Aesthetics (4/10)
    24. 6. Zipf's Law, Power Laws, and Music Aesthetics (5/10)
    25. 6. Zipf's Law, Power Laws, and Music Aesthetics (6/10)
    26. 6. Zipf's Law, Power Laws, and Music Aesthetics (7/10)
    27. 6. Zipf's Law, Power Laws, and Music Aesthetics (8/10)
    28. 6. Zipf's Law, Power Laws, and Music Aesthetics (9/10)
    29. 6. Zipf's Law, Power Laws, and Music Aesthetics (10/10)
  10. III. Social Aspects of Music Data Mining
    1. 7. Web-Based and Community-Based Music Information Extraction (1/7)
    2. 7. Web-Based and Community-Based Music Information Extraction (2/7)
    3. 7. Web-Based and Community-Based Music Information Extraction (3/7)
    4. 7. Web-Based and Community-Based Music Information Extraction (4/7)
    5. 7. Web-Based and Community-Based Music Information Extraction (5/7)
    6. 7. Web-Based and Community-Based Music Information Extraction (6/7)
    7. 7. Web-Based and Community-Based Music Information Extraction (7/7)
    8. 8. Indexing Music with Tags (1/6)
    9. 8. Indexing Music with Tags (2/6)
    10. 8. Indexing Music with Tags (3/6)
    11. 8. Indexing Music with Tags (4/6)
    12. 8. Indexing Music with Tags (5/6)
    13. 8. Indexing Music with Tags (6/6)
    14. 9. Human Computation for Music Classification (1/5)
    15. 9. Human Computation for Music Classification (2/5)
    16. 9. Human Computation for Music Classification (3/5)
    17. 9. Human Computation for Music Classification (4/5)
    18. 9. Human Computation for Music Classification (5/5)
  11. IV. Advanced Topics
    1. 10. Hit Song Science (1/5)
    2. 10. Hit Song Science (2/5)
    3. 10. Hit Song Science (3/5)
    4. 10. Hit Song Science (4/5)
    5. 10. Hit Song Science (5/5)
    6. 11. Symbolic Data Mining in Musicology (1/5)
    7. 11. Symbolic Data Mining in Musicology (2/5)
    8. 11. Symbolic Data Mining in Musicology (3/5)
    9. 11. Symbolic Data Mining in Musicology (4/5)
    10. 11. Symbolic Data Mining in Musicology (5/5)

Product information

  • Title: Music Data Mining
  • Author(s): Tao Li, Mitsunori Ogihara, George Tzanetakis
  • Release date: July 2011
  • Publisher(s): CRC Press
  • ISBN: 9781439835555