Abstract
Due to the vast number of makeup videos online, finding a suitable one is challenging. To develop a makeup video recommendation service, we must establish a method for calculating the similarities between the makeup process. This paper proposes a Make-up FLOW system, which represents makeup procedures using a flowchart style structure. We evaluated its effectiveness in recommending videos from 103 tutorial videos based on process similarities. The findings showed a weak correlation using the Levenshtein distance in the first half of the process, suggesting that the process similarity may help recommend multiple information and sort search results.
Artifacts
Information
Book title
Collaboration Technologies and Social Computing (CollabTech 2024)
Volume
LNCS 14890
Pages
229–236
Date of issue
2024/08/20
Date of presentation
2024/09/13
Location
Barcelona, Spain
Citation
Sayaka Takano, Satoshi Nakamura. Make-Up FLOW: A Beauty YouTubers’ Video Recommendation Method Based on Make-Up Flowcharts, Collaboration Technologies and Social Computing (CollabTech 2024), Vol.LNCS 14890, pp.229–236, 2024.