Chatbot - beauty skin care products recommendations

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 p...

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Bibliographic Details
Main Author: Liew, Yi Kei
Format: Final Year Project / Dissertation / Thesis
Published: 2021
Subjects:
Online Access:http://eprints.utar.edu.my/4739/
http://eprints.utar.edu.my/4739/1/fyp_IB_2021_LYK.pdf
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author Liew, Yi Kei
author_facet Liew, Yi Kei
author_sort Liew, Yi Kei
building UTAR Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-15T19:35:11Z
format Final Year Project / Dissertation / Thesis
id utar-4739
institution Universiti Tunku Abdul Rahman
institution_category Local University
last_indexed 2025-11-15T19:35:11Z
publishDate 2021
recordtype eprints
repository_type Digital Repository
spelling utar-47392023-01-04T13:28:31Z Chatbot - beauty skin care products recommendations Liew, Yi Kei T Technology (General) 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. 2021-01 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4739/1/fyp_IB_2021_LYK.pdf Liew, Yi Kei (2021) Chatbot - beauty skin care products recommendations. Final Year Project, UTAR. http://eprints.utar.edu.my/4739/
spellingShingle T Technology (General)
Liew, Yi Kei
Chatbot - beauty skin care products recommendations
title Chatbot - beauty skin care products recommendations
title_full Chatbot - beauty skin care products recommendations
title_fullStr Chatbot - beauty skin care products recommendations
title_full_unstemmed Chatbot - beauty skin care products recommendations
title_short Chatbot - beauty skin care products recommendations
title_sort chatbot - beauty skin care products recommendations
topic T Technology (General)
url http://eprints.utar.edu.my/4739/
http://eprints.utar.edu.my/4739/1/fyp_IB_2021_LYK.pdf