Uncertainty-Aware Heterogeneous Representation Learning in POI Recommender Systems-Reference-Cited by-同舟云学术

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Uncertainty-Aware Heterogeneous Representation Learning in POI Recommender Systems

Published:2023-07 Issue:7 Volume:53 Page:4522-4535
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Zhou Fan¹^ORCID,Qian Tangjiang¹,Mo Yuhua¹,Cheng Zhangtao¹,Xiao Chunjing²^ORCID,Wu Jin¹,Trajcevski Goce³^ORCID

Affiliation:

1. University of Electronic Science and Technology of China, Chengdu, China

2. Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng, China

3. Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA

Funder

National Natural Science Foundation of China

Science and Technology Foundation of Henan Province of China

Natural Science Foundation of Sichuan Province

National Science Foundation SWIFT

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software

Link

https://ieeexplore.ieee.org/ielam/6221021/10153807/10070746-aam.pdf

Reference57 articles.

1. Spatiotemporal Representation Learning for Translation-Based POI Recommendation

2. Recommendation via Collaborative Autoregressive Flows

3. Facial Expression Analysis under Partial Occlusion

4. Session-based recommendation via flow-based deep generative networks and Bayesian inference

5. Collaborative Variational Autoencoder for Recommender Systems

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2. Personalized Point-of-Interest Recommendation Using Improved Graph Convolutional Network in Location-Based Social Network;Electronics;2023-08-18

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