Online Recommender System for Radio Station Hosting: Experimental Results Revisited

P. 229–236.

Ignatov D. I., Nikolenko S. I., Abaev T., Konstantinova N.

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. 

 

Keywords: music recommender systems, interactive radio network, quality of service, качество обслуживания, интерактивная радиосеть, information fusion, hybrid recommender system, музыкальная рекомендательная система, слияние информации, гибридная рекомендательная система

Publication based on the results of: Social and Political Processes Online: The Structure and Content of Social Interactions (2014)

In book

Proceedings of The 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2014, 11-14 August 2014 Warsaw, Poland

Los Alamitos, Washington, Tokyo: IEEE Computer Society, 2014.