Intelligent recommendation of personalised tourist routes based on improved discrete particle swarm
by Jie Luo; Xilian Duan
International Journal of Computational Science and Engineering (IJCSE), Vol. 25, No. 6, 2022

Abstract: In order to overcome the problems of low accuracy and long time consuming in traditional personalised travel route recommendation methods, this paper proposes an intelligent recommendation of personalised tourist routes based on improved discrete particle swarm. This method analyses the key problems of tourism recommendation according to the personalised tourism characteristics, collects the information of tourists' interest, and establishes the model of tourists' interest. On this basis, the discrete particle swarm optimisation algorithm is improved, and the improved discrete particle swarm optimisation algorithm is used to select the personalised travel route, and the selection results are recommended to the passengers, so as to realise the personalised travel route intelligent recommendation. The experimental results show that the recommendation accuracy of this method is between 82.5% and 96.9%, and the recommendation time is always less than 0.5 s, which can realise the accurate and rapid recommendation of personalised tourist routes.

Online publication date: Fri, 25-Nov-2022

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