Chatbot - beauty skin care products recommendations

Liew, Yi Kei (2021) Chatbot - beauty skin care products recommendations. Final Year Project, UTAR.

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Abstract

Skincare products work differently depending on the type of skin. Therefore, the project proposes a context-aware chatbot for skincare product recommendations based on skin types. Firstly, we collect genuine product reviews dataset using a custom web crawler on cosmetic websites. The dataset is preprocessed to remove noises like null value, incomplete reviews, and unverified reviews. Then, we built a sentiment analyzer based on DistilBERT to rate beauty products based on the positive and negative scores from the products reviews. Next, we train a skin type model to detect four skin types: dry, oily, combination and natural using a CNN. Then, we trained a recommendation system using a factorization machine to automatically recommend skincare products to users based on the skin types. Lastly, we built a chatbot in Telegram for users to input their facial image for skin detection and product recommendations.

Item Type:	Final Year Project / Dissertation / Thesis (Final Year Project)
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Information and Communication Technology > Bachelor of Information Systems (Honours) Business Information Systems
Depositing User:	ML Main Library
Date Deposited:	04 Jan 2023 21:28
Last Modified:	04 Jan 2023 21:28
URI:	http://eprints.utar.edu.my/id/eprint/4739

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