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Gdańsk University of Technology

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Music Recommendation System

The paper focuses on optimization vector content feature for the music recommendation system. For the purpose of experiments a database is created consisting of excerpts of music les. They are assigned to 22 classes corresponding to dierent music genres. Various feature vectors based on low-level signal descriptors are tested and then optimized using correlation analysis and Principal Component Analysis (PCA). Results of the experiments are shown for the variety of feature vectors. Also, a music recommendatio

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Additional information

Category
Publikacja w czasopiśmie
Type
artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Language
angielski
Publication year
2014

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