Trends and characteristics of travelers visiting the city of Pereira through data mining techniques.


Authors

  • Diego Fernando Salcedo Toro Universidad Autonoma Manizales

DOI:

https://doi.org/10.22517/23447214.13251

Keywords:

—Knowledge Discovery, Unsupervised learning, Computer aided analysis, Knowledge management, Data analysis.

Abstract

This work was carried out on travelers Pereira city until 2014. With the collected data segmentation and description of travel behavior performing cluster analysis was performed subsequently classified according to trends and characteristics applying association rules and eventually were grouped by the level of expenditure, perception and satisfaction after visiting the city through cluster analysis. In the results they yielded 5 clusters from which one it was realized the analysis.

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Author Biography

Diego Fernando Salcedo Toro, Universidad Autonoma Manizales

Ingeniero de Sistemas

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Published

2017-12-30

How to Cite

Salcedo Toro, D. F. (2017). Trends and characteristics of travelers visiting the city of Pereira through data mining techniques. Scientia Et Technica, 22(4), 381–390. https://doi.org/10.22517/23447214.13251

Issue

Vol. 22 No. 4 (2017)

Section

Sistemas y Computación

License

Copyrights

The journal is free open access. The papers are published under the Creative Commons Attribution / Attribution-NonCommercial-NoDerivatives 4.0 International - CC BY-NC-ND 4.0 license. For this reason, the author or authors of a manuscript accepted for publication will yield all the economic rights to the Universidad Tecnológica of Pereira free of charge, taking into account the following:

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The transferors using ASSIGNMENT OF PATRIMONIAL RIGHTS letter declare that all the material that is part of the article is entirely free of copyright.  Therefore, the authors are responsible for any litigation or related claim to intellectual property rights. They exonerate of all responsibility to the Universidad Tecnológica of Pereira (publishing entity) and the Scientia et Technica journal. Likewise, the authors accept that the work presented will be distributed in free open access, safeguarding copyright under the Creative Commons Attribution / Recognition-NonCommercial-NoDerivatives 4.0 International - https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es license.