Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30773
Title: A fashion mix-and-match expert system for fashion retailers using fuzzy screening approach
Authors: Wong, WK 
Zeng, XH
Au, WMR
Mok, PY 
Leung, SYS 
Keywords: Expert systems
Fuzzy screening
Multi-criteria decision-making
Issue Date: 2009
Publisher: Pergamon Press
Source: Expert systems with applications, 2009, v. 36, no. 2 part 1, p. 1750-1764 How to cite?
Journal: Expert systems with applications 
Abstract: In today's fashion retailing business, providing "fashion mix-and-match" or "fashion coordination" recommendations is a 'must' strategy to enhance customer service and improve sales. In this study, a fashion mix-and-match expert system is developed to provide customers with professional and systematic mix-and-match recommendations automatically. The system can capture the knowledge and emulate the decisions of fashion designers on apparel coordination and its knowledge base can store the literal form of information. A set of attributes of the apparel for coordination are identified and formulated; their corresponding importance is also defined with designers' opinions using ordered weighted averaging operators. The Fashion Coordination Satisfaction Index is devised and computed using the fuzzy screening approach to represent the satisfaction degree of the coordinating pairs of apparel product items. The experimental results demonstrate that the proposed system can generate effective mix-and-match recommendations and is now integrated with a smart dressing system used effectively in a fashion chain store company in Hong Kong.
URI: http://hdl.handle.net/10397/30773
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2007.12.047
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