Abstract: In order to deal with the challenge of personalized tourism recommendation brought by a large number of multimedia photos and videos in the era of big data, this paper proposes a context aware personalized tourism recommendation system based on data mining. The structure can locate and summarize the tourism location according to the given geographical tag photo set of users, and establish the tourism history of each user to obtain their tourism preferences, so as to promote the tourism. The personalized query based on context aware is used to recommend the most suitable tourist destination. Through simulation analysis, the proposed method was compared with traditional data mining algorithms such as Apriori, Eclat, decision tree and logistic regression. The simulation results verify the superior performance of the proposed method, and the final average recommendation accuracy can reach about 80%.

Key words: data mining, personalized recommendation, smart tourism, context awareness