@inproceedings{a90ec214e27b44c9886a8b773ef8f05b,
title = "A Fuzzy Learning Method to Segment Visitors of a Tourist Attraction",
abstract = "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.",
keywords = "Clustering, Fuzzy, Satisfaction, Tourism",
author = "Jennifer Nguyen and Albert Armisen and German S{\'a}nchez-Hern{\'a}ndez and N. Agell and Cecilio Angulo",
note = "Funding Information: This research has been partially supported by the INVITE Research Project (TIN2016-80049-C2-1-R and TIN2016-80049-C2-2-R (AEI/FEDER, UE)), funded by the Spanish Ministry of Science and Information Technology. Publisher Copyright: {\textcopyright} 2018 The authors and IOS Press.",
year = "2018",
doi = "10.3233/978-1-61499-918-8-96",
language = "English",
isbn = "9781614999171",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "96--105",
editor = "Zoe Falomir and Enric Plaza and Karina Gibert",
booktitle = "Artificial Intelligence Research and Development",
address = "Netherlands",
}