Study On Preference Of Domestic Tourists In Sanya Based On Networktravelnote Text Mining

With the increasing improvement of the people's economic level and the development of tourism in China,individualized demand of tourist for tourism has become increasingly prominent.Mastering the law of tourists' preferences has become the key to improving the level of tourism services and meeting individualized demand of tourist for tourism.At the same time,with the popularization of Internet technology and the development of e-commerce in China,more and more tourists choose tourism products through the network,share their travel experience and record their travel experience.Therefore,the network has accumulated a large number of network travel notes based on natural language texts.These travel notes contain abundant information about tourists'behavior,which provides a new way to study tourists'preferences.How to mine the information accurately and efficiently for network travel notes becomes the key to study tourists'preferences.This thesis introduces the relevant theory and technology of text mining into the study of tourists'preferences by accumulating a large number of network travel notes rich in tourists' behavior information.The main work of this thesis are as follows:(1)The web crawler strategy,data preprocessing and affective analysis methods suitable for network travel data are studied;(2)a tourist preference mining model is constructed based on the theory of text mining;(3)Taking the data of Sanya tourists'travel notes as an example,this thesis puts forward some suggestions for the development of Sanya's tourism industry.Traditional research on tourists'preferences mainly obtains tourists' behavior data through questionnaires.The objectivity and quantity of the data can not be guaranteed.This thesis introduces the theory of network travel data and text mining into the study of tourists'preferences,which not only improves the quality of data in the traditional preference research field,but also provides a new method for grasping tourists'preferences more accurately,has great theoretical and practical significance.