Music data mining /

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, Mus...

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Bibliographic Details
Online Access: Full text (MCPHS users only)
Other Authors: Li, Tao, Ogihara, Mitsunori, 1963-, Tzanetakis, George, 1975-
Format: Electronic eBook
Language:English
Published: Boca Raton, Fla. : Taylor & Francis, 2011
Series:Chapman & Hall/CRC data mining and knowledge discovery series ; 21.
Subjects:
Local Note:ProQuest Ebook Central

MARC

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505 0 |a Front Cover; Contents; List of Figures; List of Tables; Preface; List of Contributors; I. Fundamental Topics; 1. Music Data Mining: An Introduction; 2. Audio Feature Extraction; II. Classification; 3. Auditory Sparse Coding; 4. Instrument Recognition; 5. Mood and Emotional Classification; 6. Zipf's Law, Power Laws, and Music Aesthetics; III. Social Aspects of Music Data Mining; 7. Web-Based and Community-Based Music Information Extraction; 8. Indexing Music with Tags; 9. Human Computation for Music Classification; IV. Advanced Topics; 10. Hit Song Science 
520 |a 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 successfully employ data mining techniques for the purpose of music processing.The book first covers music data mining tasks and algorithms and audio feature extraction, providing a framework for subsequent chapters. With a focus on data classificat. 
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