Int J Performability Eng ›› 2021, Vol. 17 ›› Issue (8): 695-702.doi: 10.23940/ijpe.21.08.p5.695702

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A Review on the Literature of Fashion Recommender System using Deep Learning

Angel Arul Jothi Ja,* and Razia Sulthana Aa   

  1. aDepartment of Computer Science, Birla Institute of Technology and Science Pilani Dubai Campus, 345055, UAE
  • Submitted on ; Revised on ; Accepted on
  • Contact: * E-mail address: angeljothi@dubai.bits-pilani.ac.in

Abstract: Over the years, much research has been conducted on fashion recommendation systems. Different techniques such as image processing, machine learning, or deep learning have been incorporated in the recommendation systems. Online e-stores like Amazon, eBay, etc. customize fashion recommendation systems to satisfy the daily requirements of their customers. A number of different approaches are proposed to study the purchase pattern of the customers. This article reviews various works in fashion recommenders using deep learning that are published from 2016 to 2020. Researchers have used deep learning models distinctly or by pairing with other machine learning models in building the recommendation system. The manuscript provides a brief description of the persuading deep learning models that owns a place in recommendation systems.

Key words: deep learning, recommendation system, generative adversarial network, convolutional neural network, autoencoder, long short term memory, machine learning