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A fuzzy learning method to segment visitors of a tourist attraction

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10.3233/978-1-61499-918-8-96
 
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Nguyen, Jennifer
Armisen Morell, Albert
Sánchez Hernández, Germán
Agell Jané, Núria
Angulo Bahón, CecilioMés informacióMés informacióMés informació
Document typeConference report
Defense date2018
Rights accessRestricted access - publisher's policy
Attribution-NonCommercial-NoDerivs 3.0 Spain
This work is protected by the corresponding intellectual and industrial property rights. Except where otherwise noted, its contents are licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
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.
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. 
URIhttp://hdl.handle.net/2117/134033
DOI10.3233/978-1-61499-918-8-96
Publisher versionhttp://ebooks.iospress.nl/volumearticle/50395
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