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Music Recommendation and Discovery
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The article was published on 2010-01-01. It has received 175 citations till now.read more
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Journal ArticleDOI
Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols
TL;DR: A comprehensive survey and analysis of the state of the art on time-aware recommender systems (TARS), and proposes a methodological description framework aimed to make the evaluation process fair and reproducible.
Towards Time-Dependant Recommendation based on Implicit Feedback
Linas Baltrunas,Xavier Amatriain +1 more
TL;DR: This work introduces a new context-aware recommendation approach called user micro-proling, which split each single user prole into several possibly overlapping sub-proles, each representing users in particular contexts.
Journal ArticleDOI
Automated Generation of Music Playlists: Survey and Experiments
Geoffray Bonnin,Dietmar Jannach +1 more
TL;DR: The results show that track and artist popularity can play a dominant role and that additional measures are required to better characterize and compare the quality of automatically generated playlists.
Journal ArticleDOI
The dynamics of correlated novelties.
TL;DR: In this article, a mathematical model that mimics the process of exploring a physical, biological, or conceptual space that enlarges whenever a novelty occurs was proposed, and the model, a generalization of Polya's urn, predicts statistical laws for the rate at which novelties happen (Heaps' law) and for the probability distribution on the space explored.
Book ChapterDOI
Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback
Balázs Hidasi,Domonkos Tikk +1 more
TL;DR: In this paper, a generic context-aware implicit feedback recommender algorithm, coined iTALS, applies a fast, ALS-based tensor factorization learning method that scales linearly with the number of non-zero elements in the tensor.