Collaborative filtering beyond the user-item matrix: A survey of the state of the art and future challenges

Y Shi, M Larson, A Hanjalic - ACM Computing Surveys (CSUR), 2014‏ - dl.acm.org
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 …

Human-centered recommender systems: Origins, advances, challenges, and opportunities

J Konstan, L Terveen - AI Magazine, 2021‏ - ojs.aaai.org
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 …

Double-scale self-supervised hypergraph learning for group recommendation

J Zhang, M Gao, J Yu, L Guo, J Li, H Yin - Proceedings of the 30th ACM …, 2021‏ - dl.acm.org
With the prevalence of social media, there has recently been a proliferation of
recommenders that shift their focus from individual modeling to group recommendation …

Recommender systems survey

J Bobadilla, F Ortega, A Hernando… - Knowledge-based systems, 2013‏ - Elsevier
Recommender systems have developed in parallel with the web. They were initially based
on demographic, content-based and collaborative filtering. Currently, these systems are …

Attentive group recommendation

D Cao, X He, L Miao, Y An, C Yang… - The 41st International ACM …, 2018‏ - dl.acm.org
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 …

Social influence-based group representation learning for group recommendation

H Yin, Q Wang, K Zheng, Z Li, J Yang… - 2019 IEEE 35th …, 2019‏ - ieeexplore.ieee.org
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 …

[ספר][B] Statistical foundations of data science

J Fan, R Li, CH Zhang, H Zou - 2020‏ - taylorfrancis.com
Statistical Foundations of Data Science gives a thorough introduction to commonly used
statistical models, contemporary statistical machine learning techniques and algorithms …

An efficient group recommendation model with multiattention-based neural networks

Z Huang, X Xu, H Zhu, MC Zhou - IEEE Transactions on Neural …, 2020‏ - ieeexplore.ieee.org
Group recommendation research has recently received much attention in a recommender
system community. Currently, several deep-learning-based methods are used in group …

Hierarchical hyperedge embedding-based representation learning for group recommendation

L Guo, H Yin, T Chen, X Zhang, K Zheng - ACM Transactions on …, 2021‏ - dl.acm.org
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 …

Fairness-aware group recommendation with pareto-efficiency

L **ao, Z Min, Z Yongfeng, G Zhaoquan… - Proceedings of the …, 2017‏ - dl.acm.org
Group recommendation has attracted significant research efforts for its importance in
benefiting a group of users. This paper investigates the Group Recommendation problem …