HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario
Joanna Alvarado-Uribe,
Andrea Gómez-Oliva,
Ari Yair Barrera-Animas,
Germán Molina,
Miguel Gonzalez-Mendoza,
María Concepción Parra-Meroño,
Antonio J. Jara
Affiliations
Joanna Alvarado-Uribe
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
Andrea Gómez-Oliva
HOP Ubiquitous S.L., Calle Luis Buñuel No. 6, 30562 Ceutí, Murcia, Spain
Ari Yair Barrera-Animas
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
Germán Molina
HOP Ubiquitous S.L., Calle Luis Buñuel No. 6, 30562 Ceutí, Murcia, Spain
Miguel Gonzalez-Mendoza
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
María Concepción Parra-Meroño
Social Sciences, Law and Business Department, Universidad Católica de Murcia (UCAM),Business Administration, Marketing and Economics, Campus de los Jerónimos, Guadalupe, 30107 Murcia, Spain
Antonio J. Jara
Institute of Information Systems, University of Applied Sciences Western Switzerland, ConEx Lab, 3960 Sierre, Switzerland
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.
