A Ubiquitous Clinic Recommendation System Using the Modified Mixed-Binary Nonlinear Programming-Feedforward Neural Network Approach

Most of the existing ubiquitous clinic recommendation (UCR) systems adopt linear mechanisms to aggregate the attribute-level performances of a clinic to evaluate the overall performance. However, such linear mechanisms may not be able to explain the choices of all patients. To solve this problem, th...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Journal of theoretical and applied electronic commerce research Ročník 16; číslo 7; s. 3282 - 3298
Hlavní autoři:	Lin, Yu-Cheng, Chen, Toly
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Curicó MDPI AG 01.12.2021
Témata:	Artificial neural networks clinic Clinics Coronaviruses COVID-19 Decision making Dentists Electronic commerce feedforward neural network Methods mixed-binary nonlinear programming Neural networks Nonlinear programming Patient satisfaction Performance evaluation Questionnaires Recommender systems ubiquitous recommendation User needs Taiwan
ISSN:	0718-1876, 0718-1876
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!