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Choosing the Right Model: A Comprehensive Analysis of Outfit Recommendation Systems

by Gursimran Kaur, Hrithik Malhotra, Tanmaya Gupta
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 12
Year of Publication: 2021
Authors: Gursimran Kaur, Hrithik Malhotra, Tanmaya Gupta
10.5120/ijca2021921413

Gursimran Kaur, Hrithik Malhotra, Tanmaya Gupta . Choosing the Right Model: A Comprehensive Analysis of Outfit Recommendation Systems. International Journal of Computer Applications. 183, 12 ( Jun 2021), 13-20. DOI=10.5120/ijca2021921413

@article{ 10.5120/ijca2021921413,
author = { Gursimran Kaur, Hrithik Malhotra, Tanmaya Gupta },
title = { Choosing the Right Model: A Comprehensive Analysis of Outfit Recommendation Systems },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2021 },
volume = { 183 },
number = { 12 },
month = { Jun },
year = { 2021 },
issn = { 0975-8887 },
pages = { 13-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number12/31978-2021921413/ },
doi = { 10.5120/ijca2021921413 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:16:35.791150+05:30
%A Gursimran Kaur
%A Hrithik Malhotra
%A Tanmaya Gupta
%T Choosing the Right Model: A Comprehensive Analysis of Outfit Recommendation Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 12
%P 13-20
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This Survey unravels developmental research on Fashion Recommendation Systems. (FRS). There is an introduction to the the three types of Recommendation Systems that are present: Content based, Collaborative Filtering and Hybrid Models, and a discussion on their pros and cons. Then onto discussing the challenges faced by Recommendation approaches followed by specifically the ones by Fashion Recommendation Systems. The need for presenting Outfit recommendation models and the importance of their accuracy is presented. Finally, a comprehensive survey of 4 types of Fashion Recommendation Systems: 1.) Collaborative Filtering 2.) Content based 3.) Hybrid 4.) Ontology based. A presentation of these with examples for representative algorithms of each category, and analysis of their predictive performance and their ability to address the challenges is carried out.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Recommendation System Fashion Collaborative Filtering Content-based Filtering Hybrid Filtering Ontology Deeplearning Visual Features

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