Results 81 to 90 of about 975 (190)

RETRACTED: Next Point of Interest (POI) Recommendation System Driven by User Probabilistic Preferences and Temporal Regularities

Mathematics
The Point of Interest (POI) recommendation system is a critical tool for enhancing user experience by analyzing historical behaviors, social network data, and real-time location information with the increasing demand for personalized and intelligent ...
Fengyu Liu, Jinhe Chen, Jun Yu, Rui Zhong   +3 more
doaj   +1 more source

Hypergraph User Embeddings and Session Contrastive Learning for POI Recommendation

IEEE Access
Internet technologies have enabled location-based social networks (LBSNs) to provide users with a variety of services. In this context, next Point-of-Interest (POI) recommendation has become a key task.
Yan Zhang, Bin Wang, Qian Zhang, Sulei Zhu, Yan Ma   +4 more
doaj   +1 more source

NE-DCHL: Nonlinear Enhanced Disentangled Contrastive Hypergraph Learning for Next Point-of-Interest Recommendation

Information
Next Point-of-Interest (POI) recommendation is a crucial task in personalized location-based services, aiming to predict the next POI that a user might visit based on their historical trajectories. Although sequence models and Graph Neural Networks (GNNs)
Hongwei Zhang, Guolong Wang, Xiaofeng Yan   +2 more
doaj   +1 more source

Trajectory- and Friendship-Aware Graph Neural Network with Transformer for Next POI Recommendation

ISPRS International Journal of Geo-Information
Next point-of-interest (POI) recommendation aims to predict users’ future visitation intentions based on historical check-in trajectories. However, this task faces significant challenges, including coarse-grained user interest representation ...
Chenglin Yu, Lihong Shi, Yangyang Zhao
doaj   +1 more source

Multi-Slot Memory With Dynamic Gating: A Multi-Task Framework for Interpretable Sequential Recommendation in Niche POI Scenarios

IEEE Access
Sequential point-of-interest (POI) recommendation in niche cultural-tourism settings must capture users’ parallel interests and rapid intent shifts. This study proposes a transparent multi-task framework that combines a multi-slot user memory with
Zhaoqi Ma, Jiansong Tang, Ryosuke Saga
doaj   +1 more source

CaST-POI: Candidate-Conditioned Spatiotemporal Modeling for Next POI Recommendation

<div> Next Point-of-Interest (POI) recommendation plays a crucial role in location-based services by predicting users' future mobility patterns. Existing methods typically compute a single user representation from historical trajectories and use it to score all candidate POIs uniformly.
Zhenyu Yu, Chunlei Meng, Yangchen Zeng, Mohd Yamani Idna Idris, Shuigeng Zhou   +4 more
openaire   +2 more sources

Spatio-temporal intention learning for recommendation of next point-of-interest

Geo-spatial Information Science
Next point-of-interest (POI) recommendation has been applied by many internet companies to enhance the user travel experience. Recent research advocates deep-learning methods to model long-term check-in sequences and mine mobility patterns of people to ...
Hao Li, Peng Yue, Shangcheng Li, Chenxiao Zhang, Can Yang   +4 more
doaj   +1 more source

TOOL4POI: A Tool-Augmented LLM Framework for Next POI Recommendation

CoRR
A critical technical error was discovered during our internal review, leading to unreliable experimental results. The issue cannot be resolved, and the paper has also been formally withdrawn from AAAI 2026.
Wang, Dongsheng, Gao, Shen, Huang, Chengrui, Huang, Yuxi, Feng, Ruixiang, Shang, Shuo   +5 more
openaire   +2 more sources

MAS4POI: a Multi-Agents Collaboration System for Next POI Recommendation

LLM-based Multi-Agent Systems have potential benefits of complex decision-making tasks management across various domains but their applications in the next Point-of-Interest (POI) recommendation remain underexplored. This paper proposes a novel MAS4POI system designed to enhance next POI recommendations through multi-agent interactions.
Yuqian Wu, Yuhong Peng, Jiapeng Yu, Raymond S. T. Lee   +3 more
openaire   +2 more sources

SEAGET: Seasonal and active hours guided graph enhanced transformer for the next POI recommendation

Array
One of the most important challenges for improving personalized services in industries like tourism is predicting users’ near-future movements based on prior behavior and current circumstances. Next POI (Point of Interest) recommendation is essential for
Alif Al Hasan, Md. Musfique Anwar
doaj   +1 more source