Title: Intelligent recommendation method for personalised tourist attractions based on cloud computing technology

Authors: Changchun Guan; Jinhua Luo

Addresses: School of Economics and Management, Sanming University, Sanming City, Fujian Province, China ' School of Economics and Management, Sanming University, Sanming City, Fujian Province, China

Abstract: In order to overcome the problems of poor recommendation results and long travel time of traditional personalised tourist attractions recommendation methods, this paper proposes an intelligent personalised tourist attractions recommendation method based on cloud computing technology. The method constructs user interest model based on knowledge map vectorisation and user interest vectorisation. In the algorithm recommendation module, based on Hadoop cloud platform, Maple-Duce is parallelised, and the Bayesian network is used to predict the user's preference for items. The probability is presented to show the possibility of the user's preference for items, and the user is recommended according to the probability, so as to complete the personalised intelligent recommendation design for tourist attractions. The experimental results show that the personalised tourist attractions intelligent recommendation method has the highest recommendation accuracy up to 99%, and reduces the travel time, the minimum time is 430 min, which is feasible to some extent.

Keywords: cloud computing technology; individualisation; tourist attractions; intelligent recommendation.

DOI: 10.1504/IJICT.2023.132141

International Journal of Information and Communication Technology, 2023 Vol.23 No.1, pp.29 - 43

Received: 24 Mar 2021
Accepted: 25 May 2021
Published online: 12 Jul 2023 *

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