Publication Date

Spring 5-22-2017

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Robert Chun

Second Advisor

Jenny Lam

Third Advisor

Nirmit Patel

Abstract

For the past few years, e-commerce has changed the way people buy and sell products. People use this business model to do business over the Internet. In this domain, Human-Computer Interaction has been gaining momentum. Lately, there has been an upsurge in agent based applications in the form of intelligent personal assistants (also known as Chatbots) which make it easier for users to interact with digital services via a conversation, in the same way we talk to humans. In e- commerce, these assistants offer mainly text-based or speech based search capabilities. They can handle search for most products, but cannot handle search that is based on product features, for instance color or pattern of a T-shirt. Most of the times, it is difficult for users to define these characteristics while searching for a product. Furthermore, a growing number of consumers rely on social media to make a purchasing decision. They try to find out what is trending right now and look for similar items. This brings us the need of a virtual shopping assistant or a shopbot which recommends products based on an image of the product provided by a user. It will be designed to provide relevant responses to the user queries by performing image recognition. This report explains the proposed approach along with the implementation for the virtual shopping assistant.

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