Interaction-Enhanced and Time-Aware Graph Convolutional Network for Successive Point-of-Interest Recommendation in Traveling Enterprises-Reference-Cited by-同舟云学术

Interaction-Enhanced and Time-Aware Graph Convolutional Network for Successive Point-of-Interest Recommendation in Traveling Enterprises

Published:2023-01 Issue:1 Volume:19 Page:635-643
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Liu Yuwen¹^ORCID,Wu Huiping²,Rezaee Khosro³^ORCID,Khosravi Mohammad R.²,Khalaf Osamah Ibrahim⁴,Khan Arif Ali⁵,Ramesh Dharavath⁶^ORCID,Qi Lianyong¹^ORCID

Affiliation:

1. College of Computer Science and Technology, China University of Petroleum, Qingdao, China

2. Shandong Provincial University Laboratory for Protected Horticulture, Weifang University of Science and Technology, Weifang, China

3. Meybod University, Meybod, Iran

4. Al-Nahrain Nanorenewable Energy Research Center, Al-Nahrain University, Baghdad, Iraq

5. M3S Empirical Software Engineering Research Unit, University of Oulu, Oulu, Finland

6. Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, India

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/9944026/09863644.pdf?arnumber=9863644

Reference34 articles.

1. Graph-Enhanced Spatial-Temporal Network for Next POI Recommendation

2. Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation

3. Factorizing personalized Markov chains for next-basket recommendation

4. LGLMF: Local Geographical Based Logistic Matrix Factorization Model for POI Recommendation

5. Towards real-time demand-aware sequential POI recommendation

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