Lipstick color suggested using hybrid hidden Markov model

Cardiometry

article

Aanchal Khatreja¹  Preeti Mulay¹ 

[1] Symbiosis Institute of Technology, Symbiosis International ,(Deemed University)

关键词: Hybrid Recommendation;    Hidden Markov Model;    Collaborative Filtering;    K-Means Clustering;    Shannon Information gain;   

DOI  :  10.18137/cardiometry.2022.22.421428

学科分类：环境科学（综合）

来源: Russian New University

【 摘 要 】

In today’s lifestyle, facial makeup plays an important role in enhancing visual attractiveness a nd boosting one's self-esteem. Makeup is known as the second skin of the women, and that too lipstick is a soul of the makeup. According to a survey, an average urban woman spends almost one year and three months of her life just wearing makeup. This much of the time is due to decision-making and choosing the best makeup style that would fit a particular age, skin complexion, profession, and occasion, requiring high imagination and full art. Many makeup recommendations systems exist, but no solitary system has existed to recommend a lipstick color properly to solve this problem computationally. Therefore, as a tiny step towards helping women save their time in decision-making, the proposed model puts forward an idea of a hybrid recommendation model for lipsticks alone. This proposed methodology uses a hidden Markov model to unleash the possible color of the lipsticks based on the given attributes. The collaborative filtering system catalyzes the process to recommend the best lipstick colors using a hybrid recommendation model.

【 授权许可】

CC BY