학술논문

Recommender System Based on User Evaluations and Cosmetic Ingredients
Document Type
Conference
Source
2019 4th International Conference on Information Technology (InCIT) Information Technology (InCIT), 2019 4th International Conference on. :22-27 Oct, 2019
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Skin
Moisture
Recommender systems
Information technology
Collaboration
Data mining
Registers
natural language processing
cosmetics recommender system
user review information
cosmetic ingredient information
knowledge acquisition
Language
Abstract
This study considers the compatibility between users and basic skin care products based primarily on the products’ ingredients. We have developed a product recommender system that is expected to recommend products that provide the desired cosmetic effect for different user groups depending on age and skin type. From the cosmetics review site, based on an analysis of user evaluations, we extracted the names of ingredients that are thought to have the best effect and developed a method to recommend products that include these ingredients as their main ingredients. We propose the ingredient frequency-inverse product frequency (IF-IPF) method to derive ingredients characterizing strong-effect product group. We have defined the scale “the recommended product satisfaction level” to evaluate the effectiveness of our recommendation service. As a result, our system can recommend products with a high degree of serendipity and hidden attraction, among others.