To make the travel healthier: a new tourism personalized route recommendation algorithm

Travel route planning is an important part of traveler’s tourism planning to make the travel more healthier and to improve the tourists’ satisfying and wellbeing.With the continuous accumulation of network resources, tourists are faced with the problem of information overload when they are planning the travel route. In this work, a new method of travel path mining is proposed, which takes the topic hierarchy of scenic spots and the features of scenic spots into consideration. First of all, the travel text data is captured by the network crawler software, and after the preprocessing of the data, such as word segmenting and denoising, the standardized travel data set is formed. Then, according to the location information of hot scenic spots in the travel notes, carry out the topic stratification of the scenic spots and construct the travel path data set. Finally, the travel route is excavated by taking into account the topic hierarchy and the features of a scenic spot. The experimental results show that the proposed method can effectively extract the travel route from the mass texts of travel notes.