Chatbot for clothing recommendations

Wong, Qin Yi (2023) Chatbot for clothing recommendations. Final Year Project, UTAR.

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Abstract

The use of chatbots is growing rapidly and used as an option to interact with users in the fashion industry. Due to the COVID-19 pandemic, many fashion brands have developed chatbots as their personalized messenger chatbot to provide a better consumer experience. However, some of the chatbots do not achieve customer satisfaction as they are not designed well before developing. Moreover, a lot of consumers cannot go out to try out their favourite clothing in the physical store during this covid situation. To address this challenge, a proposed chatbot for clothing recommendations as a personalized messenger chatbot will be deployed. To achieve that, a theme-based literature review on existing systems was carried out in this paper to find out the weakness of the existing systems. The proposed chatbot will be improved from the evaluation of the existing systems. Research addresses the strength and weakness of the existing systems in this paper as well as proposed solution to solve these weaknesses. The proposed chatbot can recommend suitable clothing based on the user body profiles and clothing image uploaded for female users only. A machine learning model will be trained by using RNN to classify different types of clothes. Several tools will be using in this project such as Anaconda, Jupyter Notebook, Flutter, Visual Studio Code, Firebase Storage.

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