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- W2045393371 abstract "We present a new recommender system developed for the Russian interactive radio network FMhost based on a previously proposed model. The underlying model combines a collaborative user-based approach with information from tags of listened tracks in order to match user and radio station profiles. It follows an adaptive online learning strategy based on the user history. We compare the proposed algorithms and an industry standard technique based on singular value decomposition (SVD) in terms of precision, recall, and NDCG measures, experiments show that in our case the fusion-based approach shows the best results." @default.
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- W2045393371 date "2014-08-01" @default.
- W2045393371 modified "2023-09-27" @default.
- W2045393371 title "Online Recommender System for Radio Station Hosting: Experimental Results Revisited" @default.
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- W2045393371 doi "https://doi.org/10.1109/wi-iat.2014.38" @default.
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