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  4. Vol 7, Issue 8, 2023

Design of an Intelligent Travel Path Recommendation System Based on Dijkstra Algorithm

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DOI: 10.23977/acss.2023.070814 | Downloads: 35 | Views: 365

Author(s)

Xiaoli Jiang 1

Affiliation(s)

1 Henan Vocational College of Agriculture, Zhengzhou, Henan, China

Corresponding Author

Xiaoli Jiang

ABSTRACT

The design background of the intelligent travel path recommendation system based on Dijkstra algorithm is to solve the problem of users choosing suitable routes among numerous tourist destinations. With the rapid development of the tourism industry, people’s demands for tourism experience are also increasing. However, facing numerous tourist attractions and complex transportation networks, users often find it difficult to determine the best travel route, which consumes a lot of time and energy. In order to solve this problem, an intelligent travel path recommendation system has emerged. The system utilizes the Dijkstra algorithm to quickly find the optimal route between the user’s location and destination by calculating the shortest path. At the same time, the system could also consider the personalized needs of users. Through experimental analysis, it can be seen that the evaluation is tested in five aspects: budget planning, route planning, clothing, food, housing and transportation planning, system overall, and system processing speed. The number of experimental participants is 400, and the satisfaction rate is above 308. It can be seen that the role of the system is to provide efficient and convenient tourism route recommendations, helping users save time and energy. Through this system, users can better plan their travels, reduce the occurrence of getting lost and wasting time, and improve the quality of their travel experience.

KEYWORDS

Dijkstra Algorithm, Intelligent Design, Tourism Planning, Path Recommendation, System Design

CITE THIS PAPER

Xiaoli Jiang, Design of an Intelligent Travel Path Recommendation System Based on Dijkstra Algorithm. Advances in Computer, Signals and Systems (2023) Vol. 7: 120-128. DOI: http://dx.doi.org/10.23977/acss.2023.070814.

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