Research on parking lot recommendation system based on collaborative filtering

Jingjing Yin; Ying Liao; Lizhu Yang; Juan Zhou

doi:10.1117/12.2667636

28 March 2023 Research on parking lot recommendation system based on collaborative filtering

Jingjing Yin, Ying Liao, Lizhu Yang, Juan Zhou

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 1256604 (2023) https://doi.org/10.1117/12.2667636
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

Parking lot selection is an important part of drivers' parking behavior. Building a good parking lot recommendation system can reduce the time of parking lot selection and effectively alleviate parking problems. Firstly, the process of parking lot selection and the principle of collaborative filtering are analyzed. Then, the data of drivers' preferences are collected, and the cosine similarity method is used to find similar drivers and parking lots. Finally, based on the collaborative filtering theory, using MATLAB to realize the construction of parking lot recommendation system. The results show that the recommendation system can better recommend parking lots for drivers and facilitate drivers to make decisions quickly.

Citation Download Citation

Jingjing Yin, Ying Liao, Lizhu Yang, and Juan Zhou "Research on parking lot recommendation system based on collaborative filtering", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 1256604 (28 March 2023); https://doi.org/10.1117/12.2667636

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