Using visual features based on MPEG-7 and deep learning for movie recommendation
Item features play an important role in movie recommender systems, where
recommendations can be generated by using explicit or implicit preferences of users on …
recommendations can be generated by using explicit or implicit preferences of users on …
[PDF][PDF] Using Visual Features and Latent Factors for Movie Recommendation.
Item features play an important role in movie recommender systems, where
recommendations can be generated by using explicit or implicit preferences of users on …
recommendations can be generated by using explicit or implicit preferences of users on …
Human computation for constraint-based recommenders
Abstract PeopleViews is a Human Computation based environment for the construction of
constraint-based recommenders. Constraint-based recommender systems support the …
constraint-based recommenders. Constraint-based recommender systems support the …
How to combine visual features with tags to improve movie recommendation accuracy?
Previous works have shown the effectiveness of using stylistic visual features, indicative of
the movie style, in content-based movie recommendation. However, they have mainly …
the movie style, in content-based movie recommendation. However, they have mainly …
Improving cold start recommendation by mapping feature-based preferences to item comparisons
S Kalloori, F Ricci - Proceedings of the 25th Conference on User …, 2017 - dl.acm.org
Many Recommender Systems (RSs) rely on user preference data in the form of ratings or
likes for items. Previous research has shown that item comparisons can also be effectively …
likes for items. Previous research has shown that item comparisons can also be effectively …
Recommendations with optimal combination of feature-based and item-based preferences
Many recommender systems rely on item ratings to predict users' preferences and generate
recommendations. However, users often express preferences by referring to features of the …
recommendations. However, users often express preferences by referring to features of the …
SCFM: Social and crowdsourcing factorization machines for recommendation
With the rapid development of social networks, the exponential growth of social information
has attracted much attention. Social information has great value in recommender systems to …
has attracted much attention. Social information has great value in recommender systems to …
What makes a good movie recommendation? Feature selection for content-based filtering
M Gawinecki, W Szmyd, U Żuchowicz… - Similarity Search and …, 2021 - Springer
Nowadays, recommendation systems are becoming ubiquitous, especially in the
entertainment industry, such as movie streaming services. In More-Like-This …
entertainment industry, such as movie streaming services. In More-Like-This …
Fashion recommender systems in cold start
M Elahi, L Qi - Fashion Recommender Systems, 2020 - Springer
With the rapid growth of online market for clothing, footwear, hairstyle, and makeup,
consumers are getting increasingly overwhelmed with the volume, velocity and variety of …
consumers are getting increasingly overwhelmed with the volume, velocity and variety of …
Towards evaluating user profiling methods based on explicit ratings on item features
LL Costanzo, Y Deldjoo, MF Dacrema… - arXiv preprint arXiv …, 2019 - arxiv.org
In order to improve the accuracy of recommendations, many recommender systems
nowadays use side information beyond the user rating matrix, such as item content. These …
nowadays use side information beyond the user rating matrix, such as item content. These …