OPEN ACCESS
Along with the rapid development of Internet of Things, the informationization process of travel industry has been speeded up. In the face of the challenge of big data, the recommendation of intelligent travel service has been highly praised. Under the environment of Internet of Things, this study deals with the travel data based on Hadoop, then sets up the relational data tool and distributed cluster, and configures it to ensure that the program can operate well on the cluster. The operation mechanism and programming method of MapReduce are adopted as the core algorithm. At the same time, the classical FP-Growth data mining algorithm is parallelized, and then the recommendation travel information service is realized. The recommendation system is more integrated and the provided service is more comprehensive and personalized, which makes the travel service platform more humanized and experience better for users.
internet of things, intelligent travel, recommendation platform, hadoop
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