A survey on adversarial recommender systems: from attack/defense strategies to generative adversarial networks

Y Deldjoo, TD Noia, FA Merra - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Latent-factor models (LFM) based on collaborative filtering (CF), such as matrix factorization
(MF) and deep CF methods, are widely used in modern recommender systems (RS) due to …

Generative adversarial networks for spatio-temporal data: A survey

N Gao, H Xue, W Shao, S Zhao, KK Qin… - ACM Transactions on …, 2022 - dl.acm.org
Generative Adversarial Networks (GANs) have shown remarkable success in producing
realistic-looking images in the computer vision area. Recently, GAN-based techniques are …

Enhancing social recommendation with adversarial graph convolutional networks

J Yu, H Yin, J Li, M Gao, Z Huang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Social recommender systems are expected to improve recommendation quality by
incorporating social information when there is little user-item interaction data. However …

Graph-enhanced spatial-temporal network for next POI recommendation

Z Wang, Y Zhu, Q Zhang, H Liu, C Wang… - ACM Transactions on …, 2022 - dl.acm.org
The task of next Point-of-Interest (POI) recommendation aims at recommending a list of POIs
for a user to visit at the next timestamp based on his/her previous interactions, which is …

Curriculum meta-learning for next POI recommendation

Y Chen, X Wang, M Fan, J Huang, S Yang… - Proceedings of the 27th …, 2021 - dl.acm.org
Next point-of-interest (POI) recommendation is a hot research field where a recent emerging
scenario, next POI to search recommendation, has been deployed in many online map …

A survey on deep learning based Point-of-Interest (POI) recommendations

MA Islam, MM Mohammad, SSS Das, ME Ali - Neurocomputing, 2022 - Elsevier
Abstract Location-based Social Networks (LBSNs) enable users to socialize with friends and
acquaintances by sharing their check-ins, opinions, photos, and reviews. A huge volume of …

Learning graph-based geographical latent representation for point-of-interest recommendation

B Chang, G Jang, S Kim, J Kang - Proceedings of the 29th ACM …, 2020 - dl.acm.org
Several geographical latent representation models that capture geographical influences
among points-of-interest (POIs) have been proposed. Although the models improve POI …

Influence-driven data poisoning for robust recommender systems

C Wu, D Lian, Y Ge, Z Zhu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recent studies have shown that recommender systems are vulnerable, and it is easy for
attackers to inject well-designed malicious profiles into the system, resulting in biased …

Point-of-interest preference model using an attention mechanism in a convolutional neural network

AB Kasgari, S Safavi, M Nouri, J Hou, NT Sarshar… - Bioengineering, 2023 - mdpi.com
In recent years, there has been a growing interest in develo** next point-of-interest (POI)
recommendation systems in both industry and academia. However, current POI …

Context-aware recommender systems: From foundations to recent developments

G Adomavicius, K Bauman, A Tuzhilin… - Recommender systems …, 2021 - Springer
The importance of contextual information has been recognized by researchers and
practitioners in many disciplines, including e-commerce, personalization, information …