Results 101 to 110 of about 443,564 (206)

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

Generative Next POI Recommendation with Semantic ID

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2
Point-of-interest (POI) recommendation systems aim to predict the next destinations of user based on their preferences and historical check-ins. Existing generative POI recommendation methods usually employ random numeric IDs for POIs, limiting the ability to model semantic relationships between similar locations.
Dongsheng Wang, Yuxi Huang, Shen Gao, Yifan Wang, Chengrui Huang, Shuo Shang   +5 more
openaire   +2 more sources

Context-aware attention-based data augmentation for POI recommendation

, 2019
With the rapid growth of location-based social networks (LBSNs), Point-Of-Interest (POI) recommendation has been broadly studied in this decade. Recently, the next POI recommendation, a natural extension of POI recommendation, has attracted much ...
Yadan Luo, Shazia Sadiq, Sadiq, Shazia, Yang Li, Zhang, Zheng, Zheng Zhang, Peng Cui, Cui, Peng, Luo, Yadan, Li, Yang   +9 more
core   +1 more source

Personalized recommendation of PoIs to people with autism [PDF]

Communications of the ACM, 2022
openaire   +2 more sources

TransTARec: Time-Adaptive Translating Embedding Model for Next POI Recommendation [PDF]

The rapid growth of location acquisition technologies makes Point-of-Interest(POI) recommendation possible due to redundant user check-in records. In this paper, we focus on next POI recommendation in which next POI is based on previous POI.
Sun, Yiping
core   +1 more source

Bi-Level Graph Structure Learning for Next POI Recommendation

Next point-of-interest (POI) recommendation aims to predict a user\u27s next destination based on sequential check-in history and a set of POI candidates.
Tao, Xiang, Zhu, Yanqiao, Liu, Qiang, Zhang, Mengdi, Wang, Liang, Wu, Shu   +5 more
core   +1 more source

Next point of interest (POI) recommendation

, 2020
Next Point-of-Interest (POI) Recommendation systems nowadays often assume that the users' check-in records are accurate. However, the accuracy and certainty of a user's check-in history may not be guaranteed in a real-world application due to various ...
Wu, Ziqing
core  

Accurate POI recommendation for random groups with improved graph neural networks and a multi-negotiation model. [PDF]

Sci Rep
Song X, Liu Z, Meng L, Chu D, Yu J, Sheng QZ.   +5 more
europepmc   +1 more source

GeoMamba: Toward Efficient Geography-Aware Sequential POI Recommendation

“Where to go next” is the fundamental problem in sequential point-of-interest (POI) recommendation, which takes as input the individual check-in history, mines the dynamic preference and suggests the expected POI for the next step behavior.
Jiubing Chen, Jianxin Shang, Haoyu Wang
core   +1 more source

Familiarity-aware POI Recommendation in Urban Neighborhoods

Journal of Information Processing, 2017
Jungkyu Han, Hayato Yamana
openaire   +2 more sources