ABSTRACT

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

part I|2 pages

Fundamental Topics

chapter 1|40 pages

Music Data Mining: An Introduction

ByTao Li, Lei Li

chapter 2|32 pages

Audio Feature Extraction

ByGeorge Tzanetakis

part II|2 pages

Classification

chapter 3|18 pages

Auditory Sparse Coding

BySteven R. Ness, Thomas C. Walters, Richard F. Lyon

chapter 4|40 pages

Instrument Recognition

ByJayme Garcia Arnal Barbedo

chapter 5|34 pages

Mood and Emotional Classification

ByMitsunori Ogihara, Youngmoo Kim

chapter 6|48 pages

Zipf’s Law, Power Laws, and Music Aesthetics

ByBill Manaris, Patrick Roos, Dwight Krehbiel, Thomas Zalonis, and J.R. Armstrong

part III|2 pages

Social Aspects of Music Data Mining

chapter 7|32 pages

Web-Based and Community-Based Music Information Extraction

ByMarkus Schedl

chapter 8|30 pages

Indexing Music with Tags

ByDouglas Turnbull

chapter 9|22 pages

Human Computation for Music Classification

ByEdith Law

part IV|2 pages

Advanced Topics

chapter 10|22 pages

Hit Song Science

ByFranc¸ois Pachet

chapter 11|21 pages

Symbolic Data Mining in Musicology

ByIan Knopke and Frauke Ju¨rgensen