GNN-based long and short term preference modeling for next-location prediction

J Liu, Y Chen, X Huang, J Li, G Min - Information Sciences, 2023 - Elsevier
Next-location prediction is a special task of the next POIs recommendation. Different from
general recommendation tasks, next-location prediction is highly context-dependent:(1) …

Deep learning-based collaborative filtering recommender systems: A comprehensive and systematic review

A Torkashvand, SM Jameii, A Reza - Neural Computing and Applications, 2023 - Springer
Nowadays, the volume of online information is growing and it is difficult to find the required
information. Effective strategies such as recommender systems are required to overcome …

Toward point-of-interest recommendation systems: A critical review on deep-learning Approaches

S Safavi, M Jalali, M Houshmand - Electronics, 2022 - mdpi.com
In recent years, location-based social networks (LBSNs) that allow members to share their
location and provide related services, and point-of-interest (POIs) recommendations which …

[HTML][HTML] Accuracy-diversity trade-off in recommender systems via graph convolutions

E Isufi, M Pocchiari, A Hanjalic - Information Processing & Management, 2021 - Elsevier
Graph convolutions, in both their linear and neural network forms, have reached state-of-the-
art accuracy on recommender system (RecSys) benchmarks. However, recommendation …

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 developing next point-of-interest (POI)
recommendation systems in both industry and academia. However, current POI …

GNN at the edge: Cost-efficient graph neural network processing over distributed edge servers

L Zeng, C Yang, P Huang, Z Zhou… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
Edge intelligence has arisen as a promising computing paradigm for supporting
miscellaneous smart applications that rely on machine learning techniques. While the …

Contrastive trajectory learning for tour recommendation

F Zhou, P Wang, X Xu, W Tai, G Trajcevski - ACM Transactions on …, 2021 - dl.acm.org
The main objective of Personalized Tour Recommendation (PTR) is to generate a sequence
of point-of-interest (POIs) for a particular tourist, according to the user-specific constraints …

A top-k POI recommendation approach based on LBSN and multi-graph fusion

J Fang, X Meng, X Qi - Neurocomputing, 2023 - Elsevier
POI (Point of Interest) recommendation is a basic and on-going issue in LBSN (Location-
based Social Network) services. In this paper, a novel POI recommendation approach which …

Location recommendation based on mobility graph with individual and group influences

X Pan, X Cai, K Song, T Baker… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
With the rapid development of mobile technology, it is very convenient to share people's
current locations by checking-in on Location-Based Social Networks (LBSNs). Using users' …

DeePOF: A hybrid approach of deep convolutional neural network and friendship to Point‐of‐Interest (POI) recommendation system in location‐based social networks

S Safavi, M Jalali - Concurrency and Computation: Practice …, 2022 - Wiley Online Library
Today, millions of active users spend a percentage of their time on location‐based social
networks like Yelp and Gowalla and share their rich information. They can easily learn about …