IJBTT

An Organized Recommender System for Nigerian Fashion using Machine Learning
	© 2020 by IJCTT Journal
	Volume-68 Issue-4
	Year of Publication : 2020
	Authors : Onuodu Friday Eleonu, Ajaba Ferdinard Ebuara
	DOI :  10.14445/22312803/IJCTT-V68I4P131

How to Cite?

Onuodu Friday Eleonu, Ajaba Ferdinard Ebuara, "An Organized Recommender System for Nigerian Fashion using Machine Learning," International Journal of Computer Trends and Technology, vol. 68, no. 4, pp. 1-2, 2020. Crossref, https://doi.org/10.14445/22312803/IJCTT-V68I4P101

Abstract
Recommender Systems are everywhere. If any computer user has ever looked for books on Amazon or browsed through posts on Facebook, then that user has used a recommendation system without even knowing it. A major problem facing the Nigerian Fashion Industry is the unavailability of an Organized Recommender System that is enabled by Machine Learning. This technique is needed to enable fashion clients customize the system in order to extract specific and preferred fashion products and services. Secondly, lack of the system has also contributed to poor-decision processes among clients of the fashion industry. In this work, we developed an Organized Recommender Systems for Nigeria Fashion Industry using Machine Learning Techniques. We adopted Structured System Analysis and Design Methodology (SSADM) in his approach and further implemented with JAVA Programming Language, JavaScript and MySQL Relational Database Management System as our backend. Our results show that the role of Machine Learning in Organized Recommender Systems encompasses the supervision of transactions beyond human capabilities. In addition, this work could be of great benefit to the Fashion Entrepreneurs and to Clients in Diaspora as the work will provide them with useful information on how they can customize the system and extract specific and preferred fashion products and services.

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Keywords
Fashion, Machine Learning, Nigerian, Organized, Recommender System.