NL repository
menu
검색
Library
Browse
Communities & Collections
By Date
Authors
Titles
Subject
My Repository
My Account
Receive email updates
Edit Profile
DSpace at EWHA
사회과학대학
소비자학전공
Journal papers
View : 639 Download: 0
A big data based cosmetic recommendation algorithm
Title
A big data based cosmetic recommendation algorithm
Authors
Yoon J.
;
Joung S.
Ewha Authors
정순희
SCOPUS Author ID
정순희
Issue Date
2020
Journal Title
Journal of System and Management Sciences
ISSN
1816-6075
Citation
Journal of System and Management Sciences vol. 10, no. 2, pp. 40 - 52
Keywords
Big data
;
Cosmetics consumer
;
Recommendation algorithm
;
Similarity algorithm
Publisher
Success Culture Press
Indexed
SCOPUS
Document Type
Article
Abstract
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. © 2020, Success Culture Press. All rights reserved.
Appears in Collections:
사회과학대학
>
소비자학전공
>
Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML
Show full item record
Find@EWHA
트윗하기
BROWSE
Communities & Collections
By Date
Authors
Titles
Subject