Open AccessE-commerce Sites with Outfit Composition using Deep Learning Method
Author(s) -
Aparna V. Mote,
Pratima Patil
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j1146.0881019
Subject(s) - computer science , product (mathematics) , field (mathematics) , clothing , task (project management) , deep learning , artificial intelligence , engineering , geometry , mathematics , archaeology , systems engineering , pure mathematics , history
The fashion industry has developed in many fields and its growth is making an enormous promote in article of clothing company and e-commerce entity. The difficult task for IT industry in this field is designing the predictive system of data mining to model this. E-commerce uses electronic communication as well as information technology in many transactions for creating, transforming or for redefining the relationships between individuals and organizations. It simply means buying of products, services and information and selling them through computer network. It is totally changing the traditional approach of business. The main change in business is noticeable growth and it has many significant effects on environment as well. This is the reason why it is so preferred in business nowadays. The important part of the proposed system is to rate the fashionable outfit individual and it is considers appearances as well as meta-data. Our approach has first implemented a system of encoding visual characteristics with the help of deep convolution network for complicated contents because it is not possible to list or to label every attribute of a image. Secondly, we proposed a multi-model deep learning framework for rich contexts of fashion outfit. We propose a system which will recommend with review comments and which product should purchase and the system will display a rating of the product.