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A survey of graph neural network based recommendation in social networks
X Li, L Sun, M Ling, Y Peng - Neurocomputing, 2023 - Elsevier
With the widespread popularization of social network platforms, user-generated content and
other social network data are growing rapidly. It is difficult for social users to select interested …
other social network data are growing rapidly. It is difficult for social users to select interested …
GNN-based long and short term preference modeling for next-location prediction
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) …
general recommendation tasks, next-location prediction is highly context-dependent:(1) …
Hierarchical multi-task graph recurrent network for next poi recommendation
Learning which Point-of-Interest (POI) a user will visit next is a challenging task for
personalized recommender systems due to the large search space of possible POIs in the …
personalized recommender systems due to the large search space of possible POIs in the …
Learning fair representations via rebalancing graph structure
Abstract Graph Neural Network (GNN) models have been extensively researched and
utilised for extracting valuable insights from graph data. The performance of fairness …
utilised for extracting valuable insights from graph data. The performance of fairness …
Point-of-interest preference model using an attention mechanism in a convolutional neural network
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 …
recommendation systems in both industry and academia. However, current POI …
Multi-view enhanced graph attention network for session-based music recommendation
Traditional music recommender systems are mainly based on users' interactions, which limit
their performance. Particularly, various kinds of content information, such as metadata and …
their performance. Particularly, various kinds of content information, such as metadata and …
Intent-aware graph neural network for point-of-interest embedding and recommendation
Point of Interest (POI) recommendation algorithms can help users find the POIs that they
prefer, and they can also help merchants to find potential customers. However, most existing …
prefer, and they can also help merchants to find potential customers. However, most existing …
Learning time slot preferences via mobility tree for next poi recommendation
Next Point-of-Interests (POIs) recommendation task aims to provide a dynamic ranking of
POIs based on users' current check-in trajectories. The recommendation performance of this …
POIs based on users' current check-in trajectories. The recommendation performance of this …
Bayes-enhanced multi-view attention networks for robust POI recommendation
POI recommendation can facilitate various Location-Based Social Network services. Existing
methods generally assume the available POI check-ins are the ground-truth depiction of …
methods generally assume the available POI check-ins are the ground-truth depiction of …
A multi-task graph neural network with variational graph auto-encoders for session-based travel packages recommendation
Session-based travel packages recommendation aims to predict users' next click based on
their current and historical sessions recorded by Online Travel Agencies (OTAs). Recently …
their current and historical sessions recorded by Online Travel Agencies (OTAs). Recently …