arXiv Open Access 2015

Large Scale Discovery of Seasonal Music From User Data

Cameron Summers Phillip Popp

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Abstrak

The consumption history of online media content such as music and video offers a rich source of data from which to mine information. Trends in this data are of particular interest because they reflect user preferences as well as associated cultural contexts that can be exploited in systems such as recommendation or search. This paper classifies songs as seasonal using a large, real-world dataset of user listening data. Results show strong performance of classification of Christmas music with Gaussian Mixture Models.

Topik & Kata Kunci

cs.IR cs.MM

Penulis (2)

Cameron Summers

Phillip Popp

Format Sitasi

APA MLA BibTeX

Summers, C., Popp, P. (2015). Large Scale Discovery of Seasonal Music From User Data. https://arxiv.org/abs/1505.00519

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Informasi Jurnal

Tahun Terbit: 2015
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓