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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
develo** algorithms that generate recommendations. The resulting research progress has …
develo** algorithms that generate recommendations. The resulting research progress has …
Human-centered recommender systems: Origins, advances, challenges, and opportunities
From the earliest days of the field, Recommender Systems research and practice has
struggled to balance and integrate approaches that focus on recommendation as a machine …
struggled to balance and integrate approaches that focus on recommendation as a machine …
Double-scale self-supervised hypergraph learning for group recommendation
With the prevalence of social media, there has recently been a proliferation of
recommenders that shift their focus from individual modeling to group recommendation …
recommenders that shift their focus from individual modeling to group recommendation …
Recommender systems survey
Recommender systems have developed in parallel with the web. They were initially based
on demographic, content-based and collaborative filtering. Currently, these systems are …
on demographic, content-based and collaborative filtering. Currently, these systems are …
Attentive group recommendation
Due to the prevalence of group activities in people's daily life, recommending content to a
group of users becomes an important task in many information systems. A fundamental …
group of users becomes an important task in many information systems. A fundamental …
Social influence-based group representation learning for group recommendation
As social animals, attending group activities is an indispensable part in people's daily social
life, and it is an important task for recommender systems to suggest satisfying activities to a …
life, and it is an important task for recommender systems to suggest satisfying activities to a …
[ספר][B] Statistical foundations of data science
Statistical Foundations of Data Science gives a thorough introduction to commonly used
statistical models, contemporary statistical machine learning techniques and algorithms …
statistical models, contemporary statistical machine learning techniques and algorithms …
An efficient group recommendation model with multiattention-based neural networks
Group recommendation research has recently received much attention in a recommender
system community. Currently, several deep-learning-based methods are used in group …
system community. Currently, several deep-learning-based methods are used in group …
Hierarchical hyperedge embedding-based representation learning for group recommendation
Group recommendation aims to recommend items to a group of users. In this work, we study
group recommendation in a particular scenario, namely occasional group recommendation …
group recommendation in a particular scenario, namely occasional group recommendation …
Fairness-aware group recommendation with pareto-efficiency
Group recommendation has attracted significant research efforts for its importance in
benefiting a group of users. This paper investigates the Group Recommendation problem …
benefiting a group of users. This paper investigates the Group Recommendation problem …