Collaborative Filtering Algorithm in the Design of Intelligent Tourism Service Robots

As an industry that can bring huge economic effects, tourism plays a very important role in many regions. With the advancement of artificial intelligence technology, it is gradually being used in the tourism industry. One of the manifestations of smart tourism is the smart tourism service robot that is currently becoming popular. This kind of robot can provide users with more personalized and intelligent travel service recommendations. In order to better design intelligent travel service robots, this article believes that collaborative filtering algorithms can be used. In order to verify the effectiveness of this method, this article conducted a comparative experiment on the recommendation accuracy between robots based on this method and regular people. The average accuracy rate of the former was 93.50%, while the average accuracy rate of the latter was only 90.79%. The gap in experimental results fully demonstrates that the collaborative filtering algorithm can indeed design intelligent tourism service robots well.