Fuzzy modeling to ‘understand’ personal preferences of mHealth users: a case study

Raoul Nuijten; Uzay Kaymak; Pieter Van Gorp; Monique Simons; Pauline van den Berg; Pascale Le Blanc

doi:10.2991/eusflat-19.2019.77

Fuzzy modeling to ‘understand’ personal preferences of mHealth users: a case study

Raoul Nuijten, Uzay Kaymak, Pieter Van Gorp, Monique Simons, Pauline van den Berg, Pascale Le Blanc

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

4 Citaten (Scopus)

187 Downloads (Pure)

Samenvatting

This case study evaluates to what extent personal preferences can be automatically derived from user event data in an mHealth setting. Based on a theoretical framework, user preferences are described using six classes. Based on this framework, a structure of six Takagi-Sugeno fuzzy inference systems was constructed and evaluated against baseline data from an official survey for measuring the framework's constructs. From this analysis, it was found that user preferences may be derived from user event data using fuzzy modeling with accuracy scores that are higher than a random predictor would typically achieve.

Originele taal-2	Engels
Titel	2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
Redacteuren	Vilem Novak, Vladimir Marik, Martin Stepnicka, Mirko Navara, Petr Hurtik
Uitgeverij	Atlantis Press
Pagina's	558-565
Aantal pagina's	8
ISBN van elektronische versie	9789462527706
DOI's	https://doi.org/10.2991/eusflat-19.2019.77
Status	Gepubliceerd - sep. 2019
Evenement	11th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2019 - Prague, Tsjechië Duur: 9 sep. 2019 → 13 sep. 2019

Publicatie series

Naam	Atlantis Studies in Uncertainty Modelling
Volume	1
ISSN van geprinte versie	2589-6644

Congres

Congres	11th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2019
Land/Regio	Tsjechië
Stad	Prague
Periode	9/09/19 → 13/09/19

Financiering

This work is partly funded by the research project GOAL (443001101), from the Netherlands Organisation for Health Research and Development (ZonMw).

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10.2991/eusflat-19.2019.77

Author versionFinale auteursversie , 408 KB
publishers versionDefinitieve gepubliceerde versie, 2,36 MB

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Nuijten, R., Kaymak, U., Van Gorp, P., Simons, M., van den Berg, P., & Le Blanc, P. (2019). Fuzzy modeling to ‘understand’ personal preferences of mHealth users: a case study. In V. Novak, V. Marik, M. Stepnicka, M. Navara, & P. Hurtik (editors), 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019) (blz. 558-565). (Atlantis Studies in Uncertainty Modelling; Vol. 1). Atlantis Press. https://doi.org/10.2991/eusflat-19.2019.77

Nuijten, Raoul ; Kaymak, Uzay ; Van Gorp, Pieter et al. / Fuzzy modeling to ‘understand’ personal preferences of mHealth users : a case study. 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019). redacteur / Vilem Novak ; Vladimir Marik ; Martin Stepnicka ; Mirko Navara ; Petr Hurtik. Atlantis Press, 2019. blz. 558-565 (Atlantis Studies in Uncertainty Modelling).

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title = "Fuzzy modeling to {\textquoteleft}understand{\textquoteright} personal preferences of mHealth users: a case study",

abstract = "This case study evaluates to what extent personal preferences can be automatically derived from user event data in an mHealth setting. Based on a theoretical framework, user preferences are described using six classes. Based on this framework, a structure of six Takagi-Sugeno fuzzy inference systems was constructed and evaluated against baseline data from an official survey for measuring the framework's constructs. From this analysis, it was found that user preferences may be derived from user event data using fuzzy modeling with accuracy scores that are higher than a random predictor would typically achieve.",

keywords = "Fuzzy inference system, MHealth, Personalization, Takagi-Sugeno",

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Nuijten, R , Kaymak, U , Van Gorp, P, Simons, M, van den Berg, P & Le Blanc, P 2019, Fuzzy modeling to ‘understand’ personal preferences of mHealth users: a case study. in V Novak, V Marik, M Stepnicka, M Navara & P Hurtik (uitgave), 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019). Atlantis Studies in Uncertainty Modelling, vol. 1, Atlantis Press, blz. 558-565, 11th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2019, Prague, Tsjechië, 9/09/19. https://doi.org/10.2991/eusflat-19.2019.77

Fuzzy modeling to ‘understand’ personal preferences of mHealth users: a case study. / Nuijten, Raoul ; Kaymak, Uzay ; Van Gorp, Pieter et al.
2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019). uitgave / Vilem Novak; Vladimir Marik; Martin Stepnicka; Mirko Navara; Petr Hurtik. Atlantis Press, 2019. blz. 558-565 (Atlantis Studies in Uncertainty Modelling; Vol. 1).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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Nuijten R , Kaymak U , Van Gorp P, Simons M, van den Berg P, Le Blanc P. Fuzzy modeling to ‘understand’ personal preferences of mHealth users: a case study. In Novak V, Marik V, Stepnicka M, Navara M, Hurtik P, redacteurs, 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019). Atlantis Press. 2019. blz. 558-565. (Atlantis Studies in Uncertainty Modelling). doi: 10.2991/eusflat-19.2019.77

Fuzzy modeling to ‘understand’ personal preferences of mHealth users: a case study

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