Personalization of the tourism experience through machine learning techniques

International Journal of Combinatorial Optimization Problems and Informatics. 2026 Open access

Read full text
Authors: Cristina Flores Amador, Ernesto Bolaños Rodríguez, Asdrúbal López‐Chau, Juan Carlos González Islas, Martín Saúl Olivera Cruz
DOI: 10.61467/2007.1558.2025.v16i4.803
Cited by: 0

Abstract

This research focuses on analysing the experiences of visitors to Alameda Central during the Easter period in order to examine the degree of personalisation of the tourist experience. To this end, the study adopts a quantitative research paradigm and a non-experimental, cross-sectional design, and applies machine learning (ML) clustering algorithms. The main conclusions suggest that ML can function as a clustering tool through which visitors are grouped according to behavioural patterns, thereby potentially informing decision-making processes. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2025.v16i4.803 Dimensions.Open Alex.

Fields of Study & Subjects

Diverse Aspects of Tourism Research Digital Marketing and Social Media Diverse Scientific Research in Ukraine

Publication details

Journal / source
International Journal of Combinatorial Optimization Problems and Informatics.
Volume
17
Issue
1
Pages
182–195
Publication date
2 January 2026