Tourism Information Resource Sharing System Based on Customer Segmentation K-Means Algorithm

Abstract

With the rapid development of China's people's economic growth, people are more and more interested in tourism. With the development of Internet and network multimedia information technology, more and more users share all kinds of tourism information through the Internet. The tour information on the Internet is growing at an exponential rate. How to subdivide customers and recommend appropriate tourism information. This paper mainly analyzes the tourism information resource sharing system of customer segmentation k-means algorithm. Using k-means algorithm to cluster the longitude and latitude of customer tourism images, the images of a certain region can be segmented into images in small regions, Because the images of the same popular landmark are close in space, customer segmentation and sorting are carried out. The experimental results show that the tourism information resource sharing system based on customer segmentation k-means algorithm increases the tourism resource sharing rate by 18%, and analyzes the user's popular surface and representative address through the algorithm. Users will also be interested in the location and heat information of popular landmarks. To obtain the location information of popular landmarks, they only need to calculate the arithmetic mean of the longitude and latitude of the image corresponding to the image clustering of popular landmarks. The result is the longitude and latitude information corresponding to the popular landmark. The tourism information resource sharing system in this paper solves the problem of difficult choice for users. It can quickly obtain effective information from huge data resources and face complex tourism data. Accurate and complete tourism data information is the premise of realizing k-means algorithm + tourism, and obtaining high-quality tourism data resources is very important.