The Application Of Bayesian Network Model In Tourism Big Data Analysis

In recent years,the rapid development of tourism has accumulated rich tourism data,analysis of the travel data will further lead to the development of tourism,so the analysis of tourism data is very significant.This paper analyzes the air ticket price data in tourism.Through the analysis of multiple flight ticket price data,found that the ticket price from 3 to 15 days before the date of departure has similar variation trend,as a result,we mainly analyze ticket price variation trend in this period.Previous research work mainly consider the influence factor of ticket prices,this paper uses the price data of previous days and builds bayesian network model to predict the future ticket price variation trend(increase,constant,decrease).The results show that the price data of the previous two days are more suitable for predicting future price changes,and the prediction results are stable,and the prediction accuracy is more than 80%.We also use neural network to forecast the price change trend,the forecasting results of two models show that the prediction accuracy of bayesian network is higher than the prediction accuracy of neural network,and the predicted results are more stable.