PDPNN: Modeling User Personal Dynamic Preference for Next Point-of-Interest Recommendation

Jinwen Zhong; Can Ma; Jiang Zhou; Weiping Wang

doi:10.1007/978-3-030-50433-5_4

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PDPNN: Modeling User Personal Dynamic Preference for Next Point-of-Interest Recommendation

Jinwen Zhong Can Ma Jiang Zhou Weiping Wang

Year: 2020 Lecture notes in computer science Pages: 45-57 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-030-50433-5_4

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Keywords:

Computer science Preference Similarity (geometry) Artificial intelligence Recommender system Recurrent neural network Term (time) Artificial neural network Point of interest Trajectory Personalization Machine learning Information retrieval Human–computer interaction World Wide Web

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Recommender Systems and Techniques

Physical Sciences → Computer Science → Information Systems

Human Mobility and Location-Based Analysis

Social Sciences → Social Sciences → Transportation

Advanced Bandit Algorithms Research

Social Sciences → Decision Sciences → Management Science and Operations Research

PDPNN: Modeling User Personal Dynamic Preference for Next Point-of-Interest Recommendation

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