Title: Prediction method of tourism destination selection behaviour based on nearest neighbour decision tree

Authors: Qun Shang

Addresses: College of Culture and Tourism, Jiangsu Vocational Institute of Commerce, Nanjing, 211168, China

Abstract: Aiming at the problems of large feature extraction error and poor prediction accuracy in tourism destination selection behaviour prediction method, a tourism destination selection behaviour prediction method based on nearest neighbour decision tree is proposed. With the help of bilinear function, the abstract tourism destination selection behaviour feature data is linearised, the freedom of linear feature data is limited, and the tourism feature is extracted through the scoring matrix. Set the characteristic data matrix, fix the characteristic data in a specific area, and determine the data weight through the cosine similarity algorithm. According to the nearest neighbour algorithm, the maximum attribute value of the selection behaviour data is determined, the tourism destination selection behaviour prediction decision tree is constructed, and the selection error is corrected with the help of the correction function to complete the behaviour prediction. The results show that the accuracy of the proposed method is 97%.

Keywords: nearest neighbour decision tree; tourist destinations; select behaviour prediction; correction function; maximum attribute value.

DOI: 10.1504/IJICT.2024.135329

International Journal of Information and Communication Technology, 2024 Vol.24 No.1, pp.21 - 32

Received: 15 Sep 2021
Accepted: 17 Nov 2021
Published online: 05 Dec 2023 *