Tourism city network association degree evaluation method based on tourist behaviors

Abstract

The invention discloses a tourist city network association degree evaluation method based on tourist behaviors. The method mainly comprises the following steps: collecting tourist data, performing abnormal value processing, reporting the completeness of tourist data collection, establishing an inter-provincial tourist association degree based on national tourist electronic contract data, forming a 31 x 31 passenger flow relationship network of multiple years by utilizing a network association analysis method, and measuring and calculating an inter-provincial bidirectional network association index; and comparing association indexes of different years to obtain a travel market aggregation effect change trend, and assessing an inter-provincial tourist flow relationship, so that planning of a travel agency in the next year can be assessed, and a problem of management disorder can be effectively solved. According to the method, a tourist city network association degree evaluation model based on tourist behaviors is constructed, through network association index measurement and calculation and in combination with opportunities and challenges in the age of Internet and tourism big data, the operation mode of the traditional tourism industry is changed to a great extent, and the future prospect is wide.

Description

technical field [0001] The invention belongs to the technical field of tourism information services, and in particular relates to a tourist city network correlation evaluation method based on tourist behavior. Background technique [0002] With the improvement of living standards, tourism has gradually become a way of entertainment for people. In recent years, the number of tourists in my country has continued to rise, and even more and more people have begun to choose overseas travel, which has driven my country's economic development and consumption to a certain extent. . Moreover, a new generation of young consumer groups is gradually emerging. They have great consumption potential in tourism, so it is necessary to predict travel preferences or regions; [0003] Patent 201910162410.9 discloses a method for predicting users’ travel intentions and types based on gradient boosting decision trees. The patent includes the following steps: Step 1. Collect user basic information...

AI Technical Summary

Problems solved by technology

This invention does not further predict the connection between provinces when predicting tourists' travel intentions, which makes it impossible for travel agencies to make a long-term plan

[0004] Due to the relatively large area of ​​China, there are 31 provinces and autonomous regions, and each province and autonomous region has its own tourist attractions. Therefore, tourists from various provinces and autonomous regions will flow with each other. For travel agencies, the flow of tourists is very important Passenger traffic and hotel accommodation of travel agencies are relatively important, so how to judge the next year's arrangements with hotels and traffic needs to be evaluated with a degree of correlation; and there is no relevant technology to deal with it, so travel agencies planning and management chaos

Images