An intelligent recommendation method of personalised tour route based on association rules Online publication date: Wed, 18-Jan-2023
by Yumei Jing
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 15, No. 1, 2023
Abstract: 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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Reasoning-based Intelligent Systems (IJRIS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook