Tourism Service System Based On Telecom Locational Data

With the rapid development of economy and the improvement of people's livelihood,tourism is gaining popularity.Big data has attracted extensive attention on smart tourism.Fully understanding the preferences and travel patterns of tourists is an important requirement for building a smart tourism service system.However,current researches on wisdom tourism are still limited to the statistical analysis,while those on exploring tourist's mobility pattern are not only less but also with simple data dimensions.Besides,most tourism service systems cannot target to a clear user group,and their function settings cannot meet the actual needs.To solve the above problems,this thesis builds a tourism service system based on the telecom locational data,including three applications for the government,enterprises and individuals,which are market analysis for tourism industry,tourist behavior analysis and intelligent travel recommendation.The main content of this system are as follows:First,we discovered the potential group tourists.Group tourists often have more regular travel route,and their mobile behaviors are very similar.Therefore,this paper proposes a method for identifying potential group tourists based on integrated community classification.By evaluating the similarities of tourists' mobility,we found out the potential group tourists,and makes a comparative analysis of the tourist behavior between group tourists and individual tourists.Secondly,we proposed a Region-Activity-Time expression method that captures the multi-dimensional information of tourists from spatial,temporal and semantic aspects,enriching the information of tourists'original trajectories and making the original trajectories with a lot of redundancy and confusion to be understood and expressed.Third,we discovered the important travel patterns of tourists.The typical travel patterns of tourists are obtained by using the sequential pattern mining algorithm.Moreover,a dissimilarity measurement for two Region-Activity-Time sequential patterns is defined to measure the difference of tourists' travel patterns in different seasons.Finally,the significant seasonal patterns can be mined.In summary,this thesis focuses on the overall goal of building a tourism service system based on the telecom locational data.The system uses multi-domain data to conduct in-depth analysis of visitor behavior and proposes a Region-Activity-Time expression method to discover tourists'typical mobile patterns and significant seasonal patterns.Finally,we take Hainan Province as a case study to demonstrate the system functions and verify the effectiveness and availability of the system.