@inbook{ba10341a43da4ea899cd6b96ed7dc99a,
title = "Automatic playlist continuation using subprofile-aware diversification",
abstract = "The ACM RecSys Challenge 2018 involves the task of automatic playlist continuation (APC), aiming to help users to create and extend their own music playlists. In this paper, we explain teamrozik's approach to the Challenge. Our approach to APC is twofold: Cold-Start-APC for short playlists and SPAD-APC for other playlists. Cold-Start-APC is a rudimentary popularity-based recommender. SPAD-APC treats playlists as if they were user profles. It builds an implicit matrix factorization model to generate initial recommendations. But it re-ranks those recommendations using Sub Profle-Aware Diversification (SPAD), which is a personalized intent-aware diversification method. The SPAD re-ranking method aims to ensure that the final set of recommendations covers different interests or tastes in the playlists of the users, which we refer to as subprofles. We show that such subprofles do exist within playlists and we show that the SPAD method achieves higher precision than matrix factorization alone.",
keywords = "Automatic playlist continuation, Diversity, Music recommender, Playlists, Subprofles",
author = "Mesut Kaya and Derek Bridge",
note = "Publisher Copyright: {\textcopyright} 2018 ACM.; 12th ACM Recommender Systems Challenge Workshop, RecSys Challenge 2018 ; Conference date: 02-10-2018 Through 02-10-2018",
year = "2018",
month = oct,
day = "2",
doi = "10.1145/3267471.3267472",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
booktitle = "Proceedings of the ACM Recommender Systems Challenge 2018, RecSys Challenge 2018",
address = "United States",
}