Paper Title
Application of K-Means Clustering to Classification of Inbound Tourists to China

Abstract
The number of inbound tourists received by China is among the top in the world, which makes China's inbound tourist market very huge. Obtaining sub-tourist markets by segmenting the tourist market is beneficial to better meet the needs of tourists, helps travel agencies make market decisions and develop markets. This paper classifies inbound tourist of China and get the sub-tourist markets by K-means clustering method. Using K-means clustering method to classify tourist samples requires collecting data on different attributes of the sample.This paper use K-means clustering to cluster the inbound tourist samples to China, which containing multiple attribute data, the clustering results are sub-tourist markets and provide appropriate policy suggestions to the tourism agencies basis the characteristics of each sub-tourist market. Keywords - Inbound Tourist, Tourism, K-means Clustering, China