A Study On The Choice Model Of One-day Tour Attractions

China has a long history,a vast territory and a wealth of tourism resources.In recent years,with the vigorous development of tourism,tourism has become a mainstream form of leisure.The advent of the information age has also brought big changes to people's tourism life,people also tend to grasp the information as the basis,combined with their own needs to make decisions.Information and needs of people have mutual influence which make the decision becomes complicated.Based on in-depth analysis of the psychology and behavior of tourists' choice,this paper establishes a model of the choice of tourist attractions on the basis of the actual investigation.The model is based on a one-day tour of Tianjin travel agency,using scientific methods to select the attractions in the product.The thesis consists of three parts as follows:1.This study first defines the concept of "one-day tour",systematic analysis of the tourists and travel in the decision-making principle,feature and decision method,combined with the actual investigation,set up a tour attractions selection model.The model includes the matching of the initial demand of tourists,the personalized recommendation of tourists and the final decision of multi attributes.2.Model matching algorithm for one-day tour.In the matching stage using the improved demand satisfaction model,matching the needs of tourists and the existing schemes;in the personalized recommendation stage adopts a collaborative filtering algorithm,using improved correlation coefficient to calculate the similarity score between users;in multi attributes decision stage using TOPSIS method to make a final decision,turning the complex factors into the factors which can be used in TOPSIS method.3.Validate the model by taking the one-day tour products of Tianjin travel agency as an example.First,collect the information of one-day tour products.Then acquire score data of 164 registered users on lvping network.Then calculate the actual demand data and the rating data of ten customers to choose the best tourist attractions for them.The calculation results of ten customers are consistent with the actual selection results,and the model is verified.