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Multimodal Temporal Fusion for Next POI Recommendation

Algorithms
The objective of the next POI recommendation is using the historical check-in sequences of users to learn the preferences and habits of users, providing a list of POIs that users will be inclined to visit next.
Fang Liu, Jiangtao Li, Tianrui Li
doaj   +2 more sources

Discovering Subsequence Patterns for Next POI Recommendation [PDF]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Next Point-of-Interest (POI) recommendation plays an important role in location-based services. State-of-the-art methods learn the POI-level sequential patterns in the user's check-in sequence but ignore the subsequence patterns that often represent the socio-economic activities or coherence of preference of the users.
Kangzhi Zhao, Yong Zhang 0002, Hongzhi Yin, Jin Wang 0007, Kai Zheng 0001, Xiaofang Zhou 0001, Chunxiao Xing   +6 more
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NEXT: a neural network framework for next POI recommendation [PDF]

Frontiers of Computer Science, 2019
The task of next POI recommendation has been studied extensively in recent years. However, developing an unified recommendation framework to incorporate multiple factors associated with both POIs and users remains challenging, because of the heterogeneity nature of these information.
Zhiqian Zhang, Chenliang Li 0005, Zhiyong Wu 0003, Aixin Sun, Dengpan Ye, Xiangyang Luo 0001   +5 more
openaire   +2 more sources

Next-POI Recommendations Matching User’s Visit Behaviour [PDF]

, 2021
AbstractWe consider the urban tourism scenario, which is characterized by limited availability of information about individuals’ past behaviour. Our system goal is to identify relevant next Points of Interest (POIs) recommendations. We propose a technique that addresses the domain requirements by using clusters of users’ visits trajectories that show ...
David Massimo, Francesco Ricci
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Decentralized Collaborative Learning Framework for Next POI Recommendation

ACM Transactions on Information Systems, 2023
Next Point-of-Interest (POI) recommendation has become an indispensable functionality in Location-based Social Networks (LBSNs) due to its effectiveness in helping people decide the next POI to visit. However, accurate recommendation requires a vast amount of historical check-in data, thus threatening user privacy as the location-sensitive
Jing Long, Tong Chen 0005, Quoc Viet Hung Nguyen, Hongzhi Yin   +3 more
openaire   +5 more sources

Kernel-based Substructure Exploration for Next POI Recommendation

2022 IEEE International Conference on Data Mining (ICDM), 2022
Point-of-Interest (POI) recommendation, which benefits from the proliferation of GPS-enabled devices and location-based social networks (LBSNs), plays an increasingly important role in recommender systems. It aims to provide users with the convenience to discover their interested places to visit based on previous visits and current status.
Wei Ju 0001, Yifang Qin, Ziyue Qiao, Xiao Luo 0001, Yifan Wang 0014, Yanjie Fu, Ming Zhang 0004   +6 more
openaire   +2 more sources

Empowering Next POI Recommendation with Multi-Relational Modeling

Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022
With the wide adoption of mobile devices and web applications, location-based social networks (LBSNs) offer large-scale individual-level location-related activities and experiences. Next point-of-interest (POI) recommendation is one of the most important tasks in LBSNs, aiming to make personalized recommendations of next suitable locations to users by ...
Zheng Huang, Jing Ma 0002, Yushun Dong, Natasha Zhang Foutz, Jundong Li   +4 more
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Using Attributes Explicitly Reflecting User Preference in a Self-Attention Network for Next POI Recommendation

ISPRS International Journal of Geo-Information, 2022
With the popularity of location-based social networks such as Weibo and Twitter, there are many records of points of interest (POIs) showing when and where people have visited certain locations.
Ruijing Li, Jianzhong Guo, Chun Liu, Zheng Li, Shaoqing Zhang   +4 more
doaj   +1 more source

A Diverse and Personalized POI Recommendation Approach by Integrating Geo-Social Embedding Relations

IEEE Access, 2020
User-POI rating matrix is one of the current research hotspot of POI recommendation algorithms, the goal of which is to obtain the POIs with the highest user satisfaction.
Xiangfu Meng, Jinfeng Fang
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Long- and Short-Term Preference Modeling Based on Multi-Level Attention for Next POI Recommendation

ISPRS International Journal of Geo-Information, 2022
The next point-of-interest (POI) recommendation is one of the most essential applications in location-based social networks (LBSNs). Its main goal is to research the sequential patterns of user check-in activities and then predict a user’s next ...
Xueying Wang, Yanheng Liu, Xu Zhou, Zhaoqi Leng, Xican Wang   +4 more
doaj   +1 more source