Contextualizing music recommendations : A collaborative filtering approach using matrix factorization and implicit ratings
Recommender systems are helpful tools employed abundantly in online applications to help users find what they want. This thesis re-purposes a collaborative filtering recommender built for incorporating social media (hash)tags to be used as a context-aware recommender, using time of day and activity...
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Format: | Others |
Language: | English |
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Linköpings universitet, Institutionen för datavetenskap
2020
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Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167068 |