Hybrid recommendation system based on human-computer interaction technology and smart tourism

With the development of information technology, people's demand for personalised and intelligent tourism experiences is increasing, and traditional recommendation systems can no longer meet this demand. This article proposes a design based on human-computer interaction technology and the concept of smart tourism, aiming to enhance users' personalised travel experience. Firstly, the study collects user preference and demand data through human-computer interaction, analyses the data using collaborative filtering algorithms, and then recommends personalised travel routes for users based on their interest characteristics, travel routes, and transportation modes. The experimental results show that the hybrid collaborative filtering algorithm proposed in this paper outperforms a single collaborative filtering algorithm in terms of recommendation accuracy, recall, coverage, and popularity, achieving the best recommendation performance at a k value of 50. Therefore, human-computer interaction technology and smart tourism concepts can help users achieve more comprehensive, accurate, and personalised travel recommendations.