Fabric retrieval system for apparel e-commerce considering Kansei information

Author:

Takatera Masayuki,Yoshida Ran,Peiffer Julie,Yamazaki Moe,Yashima Kenya,Kim KyoungOk,Miyatake Keiko

Abstract

Purpose The purpose of this paper is to create a fabric retrieval system for designers that is based on a database that includes designers’ criteria and Kansei (sense and feeling) information, designed for the selection of a fabric from a wide range in e-commerce. Design/methodology/approach The database included sensory expressions for each type of fabric taken from fashion journals and values of smoothness, softness, luster and thinness (referred to as Kansei values) for each fabric. The Kansei values were determined by a Japanese expert designer using standard fabric samples of a fabric type. The system uses two search methods to find the desired type of fabric: a category search method and a free word search method. After finding appropriate types of fabric, the user further narrows down the fabrics of the selected type to more suitable fabrics using the Kansei values. The validity of the Kansei values and the effectiveness of the system were verified by 11 professional designers from Japan and Sweden. Findings The Japanese and Swedish designers were satisfied with the fabrics retrieved for specific items and found that the system was effective. The Kansei values were similar among fashion designers and shown to be effective for fabric retrieval. Originality/value The system will allow designers to find appropriate types of fabric and to narrow their search for fabrics among selected types to find candidate fabrics easily and quickly with their Kansei values and experience without technical knowledge of fabrics.

Publisher

Emerald

Subject

Polymers and Plastics,General Business, Management and Accounting,Materials Science (miscellaneous),Business, Management and Accounting (miscellaneous)

Reference19 articles.

1. Application of cluster analysis to fabric classification;International Journal of Clothing Science and Technology,1999

2. Prediction of fabric end-use using a neural network technique;Journal of the Textile Institute,2001

3. KANSEI based clothing fabric image retrieval,2009

4. Fabric classification based on recognition using a neural network and dimensionality reduction;Textile Research Journal,1998

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