| dc.description.abstract | The thesis proposes a fashion product recommendation system presented simulated
in the form of on a web application platform with many other features such as post clothing
item to sell, to share style between users like a social media, to visualize how a product
looks like when mixed with other items, to save that collection for a later occasion in
Virtual Look section of the website.
In this work, I focus on building up a social media website with a recommendation
model run below the web application system by using Frequent itemset mining, focusing
on the information of the product to combine and generate a clothing collection for creating
an association rule. I describe an implementation of this framework on a JSON server, and
user interface as a Web Application to demonstrate this clothing recommendation system.
Lastly, I discuss the approaches to applying Frequent itemset in a dataset by trying different
algorithms to find out which is the most suitable for the model, determine the proposed
quality of the system with a Confidence value. | en_US |
