Skincare Product Recommendation System

Publication Date

Spring 4-16-2025

Presentation Length

Poster/Gallery presentation

College

College of Sciences & Mathematics

Department

Math and Computer Science, Department of

Student Level

Undergraduate

SPARK Category

Research

SPARK Session

Data Science

Presentation Type

Poster

Summary

The skincare industry is oversaturated with so many products available on the market and influencers promoting based on brand collaboration. Sponsored content on the internet especially makes it difficult to trust online reviews, and the nature of the oversaturated industry can make it challenging for users to find the right products for themselves. A skincare product recommendation system can help consumers find the best products suited to their skincare needs. The system uses cosine similarity to make recommendations to users based on factors such as skin type, concerns, product components, spending limit, and user ratings.

This recommendation system is integrated into a website where users can enter a list of their skincare preferences. Once entered, the backend processes this information and calculates cosine similarity scores against the product database. The most relevant products and their details are shown to the user in a user-friendly way. This feature allows users to make well-informed decisions on their needs to obtain the best skincare regimen.

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