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Leveraging hybrid recommenders with multifaceted implicit feedback
(Technische Universitaet Graz/Institut fuer Informationssysteme und Computer MedienGraz, 2015)
Research into recommender systems has focused on the importance of considering a variety of users’ inputs for an efficient capture of their main interests. However, most collaborative filtering efforts are related to latent ...
A semi-supervised learning algorithm for relevance feedback and collaborative image retrieval
(2015-12-11)
The interaction of users with search services has been recognized as an important mechanism for expressing and handling user information needs. One traditional approach for supporting such interactive search relies on ...
Neural Scoring of Logical Inferences from Data using Feedback
Insights derived from wearable sensors in smartwatches or sleep trackers can help users in approaching their healthy lifestyle goals. These insights should indicate significant inferences from user behaviour and their ...
SINR Bounds for Broadcast Channels with Zero-Forcing Beamforming and Limited Feedback
(Ieee-inst Electrical Electronics Engineers IncPiscatawayEUA, 2012)
Semi-supervised learning for relevance feedback on image retrieval tasks
(Ieee, 2014-01-01)
Relevance feedback approaches have been established as an important tool for interactive search, enabling users to express their needs. However, in view of the growth of multimedia collections available, the user efforts ...
Recomendação online de músicas usando feedback implícito
(Universidade Federal de Minas GeraisUFMG, 2017-03-31)
The prominent success of music streaming services has brought increasingly complex challenges for music recommendation. In particular, in a streaming setting, songs are consumed sequentially within a listening session, ...