A fuzzy learning method to segment visitors of a tourist attraction
Document typeConference report
Rights accessRestricted access - publisher's policy
We propose in this paper a method which segments demographic and contextual attributes of tourists when visiting an attraction. Clustering patterns based on categorical attributes can be challenging as it is difficult to define a distance between two categorical attributes where a natural order does not exist. Our proposed measure, based on a fuzzy aggregation operator, can be easily implemented in a hierarchical agglomerative clustering algorithm. The method has been implemented in a particular tourist attraction example with 2937 visitors.
CitationNguyen, J. [et al.]. A fuzzy learning method to segment visitors of a tourist attraction. A: International Conference of the Catalan Association for Artificial Intelligence. "Artificial Intelligence Research and Development - Current Challenges, New Trends and Applications, CCIA 2018, 21st International Conference of the Catalan Association for Artificial Intelligence, Alt Empordà, Catalonia, Spain, 8-10th October 2018.". 2018, p. 96-105.