With the improvement of people’s consumption level and the increasing development of tourism, tourism is becoming more and more popular with everyone, and everyone has more requirements for it. Everyone wants to get the best travel experience for the least money, but because of the size of the world and the number of scenic spots, people usually cannot find some potential routes that interest them. Therefore, our excavation and recommendation of tourist routes can bring convenience to users. The user recommendation system proposed in this paper is to add a word vector, study the similar scenic spots of tourists, generate a data set, and then recommend it to the user for selection. In this way, users can get a route that they are interested in but have never experienced. Through the experimental mode, we also compare the performance of the algorithm in a threshold, similar number of tourists and vector dimension, and get the best values of several indicators, which can make the algorithm reach the best state and ensure the accuracy of users’ recommendation. Then, in order to find an affordable and better route for users, we introduce the ant colony algorithm, so we can find the best path. Finally, through the experiment, we can find that the ant colony algorithm has a very good advantage, which can not only save the time for tourists to take public transport but also save the cost of tourism. Through the random survey of 10 users’ satisfaction, we can get that this has been a very good promotion.
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