A big data based cosmetic recommendation algorithm

Jiyoung Yoon, Soonhee Joung

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


The purpose of this study is to develop a recommendation system to help consumers who want to purchase cosmetics to choose cosmetics more easily and comfortably. For this purpose, the cosmetics classification of 'Hwahae App', is cosmetics application in Korea, was used and developed 'recommendation system based on similarity algorithm'. This study conducted a previous study on the algorithms that make up types and recommendation systems based on Big Data. Among the numerous cosmetics, the data on consumer choice attributes and types of cosmetics were collected through the production of 'crawling Bot'. Then, the frequency of word appearance between documents was confirmed for the unstructured data information and the skin type variables of consumers. Finally we designed a system that recommends the top five products that most closely resemble the desired product, through the combination of the selection attributes that consumers want most. This study has practical value to help customers and academic meaning of recommendation system using bigdata.

Original languageEnglish
Pages (from-to)40-52
Number of pages13
JournalJournal of System and Management Sciences
Issue number2
StatePublished - 2020

Bibliographical note

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  • Big data
  • Cosmetics consumer
  • Recommendation algorithm
  • Similarity algorithm


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