The Analysis And Association Application Study Of Online Travel User Data

With the rapid development of China’s online travel industry, more and more travelers are turning to internet to obtain travel information, book travel products, issue travel review and share travel experiences, so as to make a large number of travel-related network data continuously generated. Usually, these data aren’t isolated but linked to each other or has certain associations. These relations between data have large potential value. Especially in recent years, with the growing popularity of big data concept and development of big data technology, the importance of this value becomes more prominent. Currently, both domestic scholars and foreign scholars have carried on the analysis to the online travel user data from multiple perspectives, like psychology, consumer behavior, information technology, communication, economics and so on. But the findings are more concentrated in the applications of specific data, like travel reviews, search query, post and other specific types of online travel user data, as for the online travel user data itself as well as its association studies are less involved. Therefore, this thesis selected the online travel user data and its relevance as the research object.Based on the occurrence theory, this paper set to study from the perspective of generator of online travel user data (i.e., online travel user). By means of interviews and questionnaires, this paper firstly explores the path and footprints of online travel users’ network behavior and then analyzes and summarizes the data generated from different network behaviors using the method of network text analysis. It was found out that online travel user data covers every aspect of user attribute data, user network behavior characteristics and tourism activities characteristics, but the data are stored in a variety of network platforms, its value are fragmented. Therefore, how to break down barriers between the data and construct the associated data between platforms were analyzed then, in order to form relational data by the contact of user or tourist destination. On this basis, this paper further analyzes how to mine association rules and find useful correlation form the relational data, and takes Shanghai’s tourism node data as an example. Finally, the applications of data association were discussed from the perspective of tourist destination and the online travel service provider. Besides, this paper also analyzes the data barriers and technical barriers of data association applications and put forward the corresponding optimization suggestions.