Music Data Mining
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Advances in digital music technology have created challenges for effectively accessing and interacting with large collections of music and associated data. This book explores how data mining addresses these challenges by mining useful information and using it to create novel ways of interacting with large music collections. Leading experts in data mining, machine learning, and music science examine fundamental issues of classification and audio signal processing and discuss social aspects of music mining. They also present new research in instrument recognition, mood and emotion classification, and hit song prediction science.…mehr

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Produktbeschreibung
Advances in digital music technology have created challenges for effectively accessing and interacting with large collections of music and associated data. This book explores how data mining addresses these challenges by mining useful information and using it to create novel ways of interacting with large music collections. Leading experts in data mining, machine learning, and music science examine fundamental issues of classification and audio signal processing and discuss social aspects of music mining. They also present new research in instrument recognition, mood and emotion classification, and hit song prediction science.
Autorenporträt
Tao Li, Mitsunori Ogihara, George Tzanetakis