@inproceedings{f0646480cfb94e0e969929bb94270e11,
title = "Research and realization of music recommender algorithm based on hybrid collaborative filtering",
abstract = "Digital music has penetrated every aspect of people{\textquoteright}s lives and massive resources of online digital music have maintained a rapid growth rate because of the leap of Internet. The traditional music information retrieval systems, therefore, could not meet the growing needs of users. This paper combines SVD with memory-based collaborative filtering, compensates the negative effects of sparse matrices, and then forms a hybrid recommendation algorithm. Experimental results in “R3 Yahoo!Music” shows the advantage of our proposal in accuracy.",
keywords = "Hybrid collaborative filtering, KNN-based collaborative filtering, Music recommender system, SVD",
author = "Haiying Che and Zishi Wang",
note = "Publisher Copyright: {\textcopyright} 2016 Taylor \& Francis Group, London.; 1st International Congress on Signal and Information Processing, Networking and Computers, ICSINC 2015 ; Conference date: 17-10-2016 Through 18-10-2016",
year = "2016",
doi = "10.1201/b21308-26",
language = "English",
isbn = "9781138028814",
series = "Signal and Information Processing, Networking and Computers - Proceedings of the 1st International Congress on Signal and Information Processing, Networking and Computers, ICSINC 2015",
publisher = "CRC Press/Balkema",
pages = "195--202",
editor = "Na Chen and Tingting Huang",
booktitle = "Signal and Information Processing, Networking and Computers - Proceedings of the 1st International Congress on Signal and Information Processing, Networking and Computers, ICSINC 2015",
}