A Tourist Attraction Recommendation Model Combining User Interest Modeling and Heuristic Journey Planning Algorithm

Abstract

As the boost of science and technology, smart tourism is a new trend in the tourism industry. The use of tourist attraction recommendation models can provide tourists with a more convenient, personalized, and efficient travel experience. However, traditional recommendation models cannot accurately understand the needs of tourists and provide corresponding services. In response to this issue, this study proposes to construct a new type of tourist attraction recommendation model through user interest modeling and heuristic travel planning algorithms. This study verifies the performance, and the comparative experiment demonstrates that the algorithm has an accuracy of 91%, a stable accuracy of 97%, a running time of 11.5 seconds, and a total travel planning time of 193 minutes, all of which are superior to the comparative algorithms. The analysis of the usage effect of the research model shows that the accuracy reaches 98% and the total time to effect ratio is 4.47, both of which are higher than the comparison model. In summary, the proposed tourist attraction model on the ground of user interest modeling and heuristic itinerary planning algorithm has high accuracy, good itinerary planning effect, and feasibility. This model can provide personalized services for tourists to maximize their travel needs.

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