Analysis of clothing structure and management in clothing design oriented to market demand via recommendation algorithm
Yuli Hu ()
Additional contact information
Yuli Hu: Wuzhou University
Electronic Commerce Research, 2025, vol. 25, issue 4, No 17, 2825-2846
Abstract:
Abstract With the development and progress of the times, whether it is the practicality or fashion of clothing, people's requirements for clothing are getting higher and higher. Clothing is an important part of people's daily life. With the improvement of people's overall quality, there are new requirements for the overall style of clothing, such as style, color, fabric comfort, etc. Clothing design has a non-negligible impact on clothing structure and clothing management. In this paper, a collaborative filtering clothing recommendation algorithm based on image visual features is designed. The algorithm uses the matrix decomposition model to obtain the user feature partial favorability matrix and the commodity feature possession matrix through the user-item scoring information. Experiments show that compared with the benchmark algorithm Funk-SVD, the recall, precision, and F1 scores are improved. Therefore, our algorithm can effectively analyze clothing design and clothing structure management, and give better suggestions for people.
Keywords: Analysis of clothing structure; Management in clothing design; Oriented to market demand; Recommendation algorithm (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10660-023-09776-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:elcore:v:25:y:2025:i:4:d:10.1007_s10660-023-09776-4
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10660
DOI: 10.1007/s10660-023-09776-4
Access Statistics for this article
Electronic Commerce Research is currently edited by James Westland
More articles in Electronic Commerce Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().