Online Shopping System

Abstract

"During the period of Covid pandemic people still wanted to move on with their regular activities. Therefore, the technology applications were challenging part for them but to do their regular activities they had no choices so they had to move on with these challenging technology applications. And because of the Covid pandemic, more new online applications with different domains were joining the business market. Based on my research and findings the problem is most customers struggle to find a particular clothing items in traditional clothing shops for their events such as ceremonies, birthday parties, sporting events, Gatherings etc, they are wasting their time, couldn’t get a dress, selected dress is not satisfied and their traveling expenses by searching from other clothing shops based on their preferences. Based on these problem backgrounds, The project aims to analyze the problems faced by the customers. To design and develop a suitable online web application platform solution. The project aim is to develop a fashion recommendation clothing website for an online shopping system that can help customers find clothes that meet their specific needs and preferences to attend their events. To understand more about the existing solutions and technologies in use in the area, a literature review was conducted and with that, a survey with a targeted set of customers was used to review the findings. The website will use machine learning algorithms to provide personalized recommendations. The methodology followed involves collecting and analyzing data on customer behaviors and preferences, identifying relevant attributes for different clothing items. The main result of this project is the development of a recommendation website that can help customers find clothing items that meet their specific needs and preferences based on their event. This project has the potential to improve customer satisfaction and increase sales."