An intelligent recommendation method of personalised tour route based on association rules

In this paper, an intelligent recommendation method of personalised tourism routes based on association rules was proposed. Firstly, the membership matrix is constructed to mine tourist attractions, and the scope of tourist attractions is determined by attribute clustering. Secondly, the association rule algorithm is used to extract the features of scenic spots, tourists and tourist interest points to complete the personalised classification of tourist routes. Finally, the similarity of tourist routes is calculated by dynamic and static attributes, and the maximum probability scenic spots are output intelligently. The personalised recommendation method of tourist routes is optimised to realise personalised intelligent recommendation of tourist routes. The simulation results show that the proposed method has 98.5% accuracy, 97% recall rate and only 6s recommendation time. Therefore, the proposed method improves the performance of the intelligent recommendation method and has practicability. Copyright © 2023 Inderscience Enterprises Ltd.