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Adaptive Recommendation System for Tourism by Personality Type Using Deep Learning

Author

정치서, 이종용, 정계동

Journal Title

The International Journal of Internet, Broadcasting and Communication

Publication Year

2020

Topics

#Personality
#Deep learning
#Tourism

Summary

This study proposes an adaptive recommendation system using deep learning to categorize and recommend tourism types suitable for user personality types. The proposed system consists of three layers based on its core role for efficiency and ease of maintenance. By utilizing deep learning, the system enhances scalability and flexibly delivers data by connecting user personality types with tourism types.

Journal Influence

[The International Journal of Internet, Broadcasting and Communication]