A study on the comparison between two approached on fashion trend analysis

Supplemental Files
Date
2018-01-01
Authors
an, hyosun
park, minjung
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
Authors
Research Projects
Organizational Units
Journal Issue
Series
Department
Abstract

The fashion industry in the 4th industrial revolution era is shifting to a paradigm that predicts and responds to consumer demands. Big data technologies are especially receiving an increasing amount of attention in the field of fashion design. Massive user data accumulation allows designers to make more accurate predictions for the latest seasonal fashion trends. A recent study on fashion trend analysis through IT technology was published in 2015 (Lin et al., 2015). However, since the study was accomplished in the field of computer information, the results of data analysis are derived in a biased way. The purpose of this study is to examine traditional trend analysis methods and big data analysis methods in both domestic and overseas’ fashion studies and also to propose a research method for analyzing user-oriented information on fashion design trends to supplement the limitations.

Comments
Description
Keywords
Citation
DOI
Source