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Lipstick color suggested using hybrid hidden Markov model

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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.


Aanchal Khatreja, Preeti Mulay. Lipstick color suggested using hybrid hidden Markov model. Cardiometry; Issue 22; May 2022; p.421-428; DOI: 10.18137/cardiometry.2022.22.421428; Available from:


Hybrid Recommendation,  Hidden Markov Model,  Collaborative Filtering,  K-Means Clustering,  Shannon Information gain
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