NGPR: A comprehensive personalized point-of-interest recommendation method based on heterogeneous graphs

Dongjin Yu; Ting Yu; Dongjing Wang; Yi Shen

doi:10.1007/s11042-022-13088-4

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NGPR: A comprehensive personalized point-of-interest recommendation method based on heterogeneous graphs

Dongjin Yu Ting Yu Dongjing Wang Yi Shen

Year: 2022 Journal: Multimedia Tools and Applications Vol: 81 (27)Pages: 39207-39228 Publisher: Springer Science+Business Media

DOI: 10.1007/s11042-022-13088-4

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Keywords:

Computer science Point of interest Leverage (statistics) Popularity Check-in Information retrieval Point (geometry) Data mining Construct (python library) Graph Recommender system Machine learning Artificial intelligence Theoretical computer science

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Recommender Systems and Techniques

Physical Sciences → Computer Science → Information Systems

Caching and Content Delivery

Physical Sciences → Computer Science → Computer Networks and Communications

Human Mobility and Location-Based Analysis

Social Sciences → Social Sciences → Transportation

NGPR: A comprehensive personalized point-of-interest recommendation method based on heterogeneous graphs

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