Fuzzy optimization to improve mobile health and wellness recommendation systems

A1 Originalartikel i en vetenskaplig tidskrift (referentgranskad)


Interna författare/redaktörer


Publikationens författare: Mezei Jozsef, Nikou Shahrokh
Förläggare: Elsevier
Publiceringsår: 2018
Tidskrift: Knowledge-Based Systems
Tidskriftsakronym: KNOSYS
Volym: 142
Artikelns första sida, sidnummer: 108
Artikelns sista sida, sidnummer: 116
eISSN: 0950-7051


Abstrakt

In this article, we focus on mobile wellness and health-related applications from the perspective of the level of imprecision present in the data used in the recommendation systems. We propose a general fuzzy optimization model based on chanced constrained optimization to design recommendation systems that can take into consideration (i) the imprecision in the data and (ii) the imprecision by which one can estimate the effect of a recommendation on the user of the system. Our proposal is one of the first to use fuzzy optimization models in health-related decision making problems and the first to define a chance constrained optimization problem for interval-valued fuzzy numbers. The proposed approach identifies a set of actions to be taken by the users in order to optimize general health-related and/or wellness condition of the user from various perspectives. The model is illustrated through the example of walking speed optimization, with an additional numerical experiment offering a comparison with traditional methods.


Nyckelord

Chance Constrained Programming, Fuzzy Optimisation, Linguistic Variables, Mobile Health an Wellness Applications

Senast uppdaterad 2019-10-12 vid 03:32