'SuitYou' provides personalized clothing recommendations to users after carefully analyzing human social behavior. A detailed research was conducted before and after the development of the application to provide accurate results to the user.
This specific recommendation system contains a custom socio-cultural algorithm that formulates the ratio of the kind of clothes the user prefers, based on user details like their hometown, their work place, and the kind of music and movies the user is interested in.
Inputs
User details.
Database of apparel from various fashion sites.
User details.
Database of apparel from various fashion sites.
System Flow
The basic idea was to extract data from a person’s Facebook page, including their hometown, workplace, the kind of movies they watch, kind of music they listen to, the places they frequently visit i.e, the events they attend and the places they check-in from.
This system was mainly designed for Indians, and the clothes were divided into four main dressing styles that correspond to the four cities of Bangalore, Delhi, Mumbai and Chennai. Using the information obtained from Facebook, we create a stereotypical persona that is matched to the clothes from the cities.
Algortihm Flow
LITERATURE SURVEY
Ø Analysis of Recommendation Algorithms for E-Commerce by Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl
Ø Amazon.com recommendations: item-to-item collaborative filtering.
The project was developed using Android Development Kit on Eclipse. The information about the user, details and product specifics of each of the items was obtained through sample databases created for the purpose of the application.
The visuals were created using Adobe Photoshop.
Mentors :
Akshay Ram - Product Strategist, Borqs
Dhyan Suman - Interaction Designer, Borqs
