TY  - JOUR
TI  - Design of an interactive fashion recommendation platform with intelligent systems
AU  - Vuruskan, Arzu
AU  - Demi̇Rki̇Ran, Gokhan
AU  - Bulgun, Ender
AU  - Ince, Turker
AU  - Guzelis, Cuneyt
T2  - Industria Textila
AB  - With the increase in customer expectations in online fashion sales, greater integration of fashion recommender systems
(RSs) allows more personalization. Design decisions rely on personal taste, as well as many other external influences,
such as trends and social media, making it challenging to adapt intelligent systems for the fashion industry. Different
methods for recommending personalized fashion items have been proposed, however, the literature still lacks an
approach for recommending expert-suggested and personalized items. In this research, an interactive web-based
platform is developed to support personalized fashion styling, focusing on users with diverse body shapes. To merge
the user’s taste and the expert’s suggestion, the proposed methodology in this research combines genetic algorithms
and machine learning techniques allowing the system to access expert knowledge (including external influences) and
incremental learning capability, by adapting to the user preferences that unfold during interaction with the system.
DA  - 2024/04/30/
PY  - 2024
DO  - 10.35530/IT.075.02.202312
DP  - DOI.org (Crossref)
VL  - 75
IS  - 02
SP  - 177
EP  - 184
SN  - 12225347
UR  - http://revistaindustriatextila.ro/images/2024/2/008%20ARZU%20VURUSKAN%20INDUSTRIA%20TEXTILA%20no.2_2024.pdf
Y2  - 2024/05/15/06:30:50
ER  -