Collaborative filtering beyond the user-item matrix: A survey of the state of the art and future challenges
Over the past two decades, a large amount of research effort has been devoted to
developing algorithms that generate recommendations. The resulting research progress has …
developing algorithms that generate recommendations. The resulting research progress has …
Context Aware Recommendation Systems: A review of the state of the art techniques
S Kulkarni, SF Rodd - Computer Science Review, 2020 - Elsevier
Recommendation systems are gaining increasing popularity in many application areas like
e-commerce, movie and music recommendations, tourism, news, advertisement, stock …
e-commerce, movie and music recommendations, tourism, news, advertisement, stock …
Factorization machines with libfm
S Rendle - ACM Transactions on Intelligent Systems and …, 2012 - dl.acm.org
Factorization approaches provide high accuracy in several important prediction problems,
for example, recommender systems. However, applying factorization approaches to a new …
for example, recommender systems. However, applying factorization approaches to a new …
Context-aware recommender systems
G Adomavicius, A Tuzhilin - Recommender systems handbook, 2010 - Springer
The importance of contextual information has been recognized by researchers and
practitioners in many disciplines, including e-commerce personalization, information …
practitioners in many disciplines, including e-commerce personalization, information …
Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering
Context has been recognized as an important factor to consider in personalized
Recommender Systems. However, most model-based Collaborative Filtering approaches …
Recommender Systems. However, most model-based Collaborative Filtering approaches …
Fast context-aware recommendations with factorization machines
The situation in which a choice is made is an important information for recommender
systems. Context-aware recommenders take this information into account to make …
systems. Context-aware recommenders take this information into account to make …
Matrix factorization techniques for context aware recommendation
Context aware recommender systems (CARS) adapt the recommendations to the specific
situation in which the items will be consumed. In this paper we present a novel context …
situation in which the items will be consumed. In this paper we present a novel context …
Context relevance assessment and exploitation in mobile recommender systems
In order to generate relevant recommendations, a context-aware recommender system
(CARS) not only makes use of user preferences, but also exploits information about the …
(CARS) not only makes use of user preferences, but also exploits information about the …
Tfmap: optimizing map for top-n context-aware recommendation
In this paper, we tackle the problem of top-N context-aware recommendation for implicit
feedback scenarios. We frame this challenge as a ranking problem in collaborative filtering …
feedback scenarios. We frame this challenge as a ranking problem in collaborative filtering …