Personalized Recommendation Of Tourism Services For The Elderly

The scale of the elderly is getting larger and larger,but its share in the entire tourism market is not high.In the background of intelligent endowment,this paper proposes a personalized recommendation of tourism services to enrich the retirement life of the elderly and flourish the tourism market.This paper uses an implicit scoring strategy and collaborative filtering recommendation algorithm to fuse the physical,psychological,and social attributes of the elderly,using age,gender,athletic ability,interest preferences,friends list,etc.,to calculate the similarity of the elderly,and then based on the history data to make recommendations.In order to make the algorithm have a good performance when the data volume is large,this paper realizes the parallelization of the algorithm on the Spark platform.At the same time,based on the theoretical basis,this paper integrates the tourism service recommendation algorithm into the intelligent endowment platform,and completes the system architecture design and the implementation of the tourism service recommendation submodule.