Data Mining Techniques Applied to Recommender Systems for Outdoor Activities: A Systematic Literature Review

Pablo Arévalo; John Calle; Marcos Orellana; Priscila Cedillo

doi:10.5220/0011045400003188

Data Mining Techniques Applied to Recommender Systems for Outdoor Activities: A Systematic Literature Review

Pablo Arévalo, John Calle, Marcos Orellana, Priscila Cedillo

Universidad del Azuay

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

Currently, many pollutants are released into the air, representing a risk to the environment and human health. There are significant volumes of data generated by the devices that monitor these pollutants. This information can represent a relevant input that allows the construction of applications, techniques, and methodologies to reach a prediction of the state of the air. On the other hand, recommender systems are present in numerous data processing methods, supporting the decision-making and promoting the improvement of the quality of service of solutions. Although several studies have been presented, no secondary studies have been proposed. Therefore, this paper presents a systematic review of the literature, which aims to identify the knowledge areas, tools, methods, and data mining approaches used in recommender systems for outdoor activities related to atmospheric pollutants. The results obtained contribute to creating new ways of recommendation systems based on the previous topics

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022
Editores	Martina Ziefle, Maurice Mulvenna, Leszek Maciaszek, Leszek Maciaszek
Editorial	Science and Technology Publications, Lda
Páginas	228-235
Número de páginas	8
ISBN (versión digital)	9789897585661
DOI	https://doi.org/10.5220/0011045400003188
Estado	Publicada - 2022
Publicado de forma externa	Sí
Evento	8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022 - Virtual, Online Duración: 23 abr. 2022 → 25 abr. 2022

Serie de la publicación

Nombre	International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings
ISSN (versión digital)	2184-4984

Conferencia

Conferencia	8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022
Ciudad	Virtual, Online
Período	23/04/22 → 25/04/22

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

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10.5220/0011045400003188

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Arévalo, P., Calle, J., Orellana, M., & Cedillo, P. (2022). Data Mining Techniques Applied to Recommender Systems for Outdoor Activities: A Systematic Literature Review. En M. Ziefle, M. Mulvenna, L. Maciaszek, & L. Maciaszek (Eds.), Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022 (pp. 228-235). (International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings). Science and Technology Publications, Lda. https://doi.org/10.5220/0011045400003188

Arévalo, Pablo ; Calle, John ; Orellana, Marcos et al. / Data Mining Techniques Applied to Recommender Systems for Outdoor Activities : A Systematic Literature Review. Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022. editor / Martina Ziefle ; Maurice Mulvenna ; Leszek Maciaszek ; Leszek Maciaszek. Science and Technology Publications, Lda, 2022. pp. 228-235 (International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings).

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title = "Data Mining Techniques Applied to Recommender Systems for Outdoor Activities: A Systematic Literature Review",

abstract = "Currently, many pollutants are released into the air, representing a risk to the environment and human health. There are significant volumes of data generated by the devices that monitor these pollutants. This information can represent a relevant input that allows the construction of applications, techniques, and methodologies to reach a prediction of the state of the air. On the other hand, recommender systems are present in numerous data processing methods, supporting the decision-making and promoting the improvement of the quality of service of solutions. Although several studies have been presented, no secondary studies have been proposed. Therefore, this paper presents a systematic review of the literature, which aims to identify the knowledge areas, tools, methods, and data mining approaches used in recommender systems for outdoor activities related to atmospheric pollutants. The results obtained contribute to creating new ways of recommendation systems based on the previous topics",

keywords = "Air Pollutants, Air Quality, Data Mining, Health, Recommending Systems",

author = "Pablo Ar{\'e}valo and John Calle and Marcos Orellana and Priscila Cedillo",

note = "Publisher Copyright: Copyright {\textcopyright} 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.; 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022 ; Conference date: 23-04-2022 Through 25-04-2022",

year = "2022",

doi = "10.5220/0011045400003188",

language = "Ingl{\'e}s",

series = "International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings",

publisher = "Science and Technology Publications, Lda",

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Arévalo, P, Calle, J, Orellana, M & Cedillo, P 2022, Data Mining Techniques Applied to Recommender Systems for Outdoor Activities: A Systematic Literature Review. En M Ziefle, M Mulvenna, L Maciaszek & L Maciaszek (eds.), Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022. International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings, Science and Technology Publications, Lda, pp. 228-235, 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022, Virtual, Online, 23/04/22. https://doi.org/10.5220/0011045400003188

Data Mining Techniques Applied to Recommender Systems for Outdoor Activities: A Systematic Literature Review. / Arévalo, Pablo; Calle, John; Orellana, Marcos et al.
Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022. ed. / Martina Ziefle; Maurice Mulvenna; Leszek Maciaszek; Leszek Maciaszek. Science and Technology Publications, Lda, 2022. p. 228-235 (International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Data Mining Techniques Applied to Recommender Systems for Outdoor Activities

T2 - 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022

AU - Arévalo, Pablo

AU - Calle, John

AU - Orellana, Marcos

AU - Cedillo, Priscila

PY - 2022

Y1 - 2022

N2 - Currently, many pollutants are released into the air, representing a risk to the environment and human health. There are significant volumes of data generated by the devices that monitor these pollutants. This information can represent a relevant input that allows the construction of applications, techniques, and methodologies to reach a prediction of the state of the air. On the other hand, recommender systems are present in numerous data processing methods, supporting the decision-making and promoting the improvement of the quality of service of solutions. Although several studies have been presented, no secondary studies have been proposed. Therefore, this paper presents a systematic review of the literature, which aims to identify the knowledge areas, tools, methods, and data mining approaches used in recommender systems for outdoor activities related to atmospheric pollutants. The results obtained contribute to creating new ways of recommendation systems based on the previous topics

AB - Currently, many pollutants are released into the air, representing a risk to the environment and human health. There are significant volumes of data generated by the devices that monitor these pollutants. This information can represent a relevant input that allows the construction of applications, techniques, and methodologies to reach a prediction of the state of the air. On the other hand, recommender systems are present in numerous data processing methods, supporting the decision-making and promoting the improvement of the quality of service of solutions. Although several studies have been presented, no secondary studies have been proposed. Therefore, this paper presents a systematic review of the literature, which aims to identify the knowledge areas, tools, methods, and data mining approaches used in recommender systems for outdoor activities related to atmospheric pollutants. The results obtained contribute to creating new ways of recommendation systems based on the previous topics

KW - Air Pollutants

KW - Air Quality

KW - Data Mining

KW - Health

KW - Recommending Systems

UR - https://www.scopus.com/pages/publications/85140989649

U2 - 10.5220/0011045400003188

DO - 10.5220/0011045400003188

M3 - Contribución a la conferencia

AN - SCOPUS:85140989649

T3 - International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings

SP - 228

EP - 235

BT - Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022

A2 - Ziefle, Martina

A2 - Mulvenna, Maurice

A2 - Maciaszek, Leszek

PB - Science and Technology Publications, Lda

Y2 - 23 April 2022 through 25 April 2022

ER -

Arévalo P, Calle J, Orellana M, Cedillo P. Data Mining Techniques Applied to Recommender Systems for Outdoor Activities: A Systematic Literature Review. En Ziefle M, Mulvenna M, Maciaszek L, Maciaszek L, editores, Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022. Science and Technology Publications, Lda. 2022. p. 228-235. (International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings). doi: 10.5220/0011045400003188

Data Mining Techniques Applied to Recommender Systems for Outdoor Activities: A Systematic Literature Review

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