1.

Record Nr.

UNINA9910461416403321

Titolo

Music data mining / / edited by Tao Li, Mitsunori Ogihara, George Tzanetakis

Pubbl/distr/stampa

Boca Raton, Fla. : , : CRC Press, , 2012

ISBN

0-429-10572-X

1-283-31161-5

9786613311610

1-4398-3555-1

Edizione

[1st edition]

Descrizione fisica

1 online resource (372 p.)

Collana

Chapman & Hall/CRC data mining and knowledge discovery series

Altri autori (Persone)

LiTao

OgiharaMitsunori <1963->

TzanetakisGeorge <1975->

Disciplina

780.285/6312

Soggetti

Musical analysis - Data processing

Data mining

Information storage and retrieval systems

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

A Chapman & Hall book.

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

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

11. Symbolic Data Mining in Musicology

Sommario/riassunto

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