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HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario

1
Computer Science Department, Tecnologico de Monterrey, School of Engineering and Sciences, Carretera Lago de Guadalupe Km. 3.5, Col. Margarita Maza de Juárez, Atizapán de Zaragoza 52926, Estado de Mexico, Mexico
2
HOP Ubiquitous S.L., Calle Luis Buñuel No. 6, 30562 Ceutí, Murcia, Spain
3
Social Sciences, Law and Business Department, Universidad Católica de Murcia (UCAM),Business Administration, Marketing and Economics, Campus de los Jerónimos, Guadalupe, 30107 Murcia, Spain
4
Institute of Information Systems, University of Applied Sciences Western Switzerland, ConEx Lab, 3960 Sierre, Switzerland
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(3), 890; https://doi.org/10.3390/s18030890
Received: 7 January 2018 / Revised: 28 February 2018 / Accepted: 7 March 2018 / Published: 17 March 2018
(This article belongs to the Special Issue Smart Decision-Making)
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Abstract

Nowadays, Physical Web together with the increase in the use of mobile devices, Global Positioning System (GPS), and Social Networking Sites (SNS) have caused users to share enriched information on the Web such as their tourist experiences. Therefore, an area that has been significantly improved by using the contextual information provided by these technologies is tourism. In this way, the main goals of this work are to propose and develop an algorithm focused on the recommendation of Smart Point of Interaction (Smart POI) for a specific user according to his/her preferences and the Smart POIs’ context. Hence, a novel Hybrid Recommendation Algorithm (HyRA) is presented by incorporating an aggregation operator into the user-based Collaborative Filtering (CF) algorithm as well as including the Smart POIs’ categories and geographical information. For the experimental phase, two real-world datasets have been collected and preprocessed. In addition, one Smart POIs’ categories dataset was built. As a result, a dataset composed of 16 Smart POIs, another constituted by the explicit preferences of 200 respondents, and the last dataset integrated by 13 Smart POIs’ categories are provided. The experimental results show that the recommendations suggested by HyRA are promising. View Full-Text
Keywords: recommendation algorithm; point-of-interest; similarity and distance measures; aggregation operator; POI category; geographical influence; tourism recommendation algorithm; point-of-interest; similarity and distance measures; aggregation operator; POI category; geographical influence; tourism
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Alvarado-Uribe, J.; Gómez-Oliva, A.; Barrera-Animas, A.Y.; Molina, G.; Gonzalez-Mendoza, M.; Parra-Meroño, M.C.; Jara, A.J. HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario. Sensors 2018, 18, 890.

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