Approaching Another Tourism Recommender
Xianfeng Chen, Liu Qing, Xiangjie Qiao · 2020
With the concurrent spread and development of Internet and a warm welcome to the Age of Big Data, Internet has become a main channel for travelers to obtain online information before traveling, but in the meantime they are often submerged in a large number of information by searching and for selecting. In this case, travel recommender system is created to solve the problem of information overload effectively. This article analyses the concept, application and development status of travel recommender systems through the collection and arrangement of relevant literature published in recent years. Also, it pays special attention to the analysis of key technologies in the system, pointing out its complexity and uniqueness an application. Besides, the limitations of recommendation methods based on collaborative filtering and content-based filtering are considered as well, then the using knowledge-based filtering or hybrid recommendation method is proposed. It also discusses the role and application of tourism decision-making theory in the recommender system, and finally puts forward a general model of travel recommender system and future research hot spots. It's wished that this research can expand the vision and serve as a reference in this field.