NDLI: Intelligent Fashion Recommender System: Fuzzy Logic in Personalized Garment Design

Content Provider	IEEE Xplore Digital Library
Author	Wang, L.C. Zeng, X.Y. Koehl, L. Chen, Y.
Copyright Year	2013
Abstract	This paper proposes a new intelligent fashion recommender system to select the most relevant garment design scheme for a specific consumer in order to deliver new personalized garment products. This system integrates emotional fashion themes and human perception on personalized body shapes and professional designers' knowledge. The corresponding perceptual data are systematically collected from professional using sensory evaluation techniques. The perceptual data of consumers and designers are formalized mathematically using fuzzy sets and fuzzy relations. The complex relation between human body measurements and basic sensory descriptors, provided by designers, is modeled using fuzzy decision trees. The fuzzy decision trees constitute an empirical model based on learning data measured and evaluated on a set of representative samples. The complex relation between basic sensory descriptors and fashion themes, given by consumers, is modeled using fuzzy cognitive maps. The combination of the two models can provide more complete information to the fashion recommender system, making it possible to evaluate if a specific body shape is relevant to a desired emotional fashion theme and which garment design scheme can improve the image of the body shape. The proposed system has been validated in a customized design and mass market selection through the evaluations of target consumers and fashion experts using a method frequently used in marketing study.
Starting Page	95
Ending Page	109
Page Count	15
File Size	4761978
File Format	PDF
ISSN	21682291
Volume Number	45
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Recommender systems Clothing Decision trees Computational modeling Predictive models sensory evaluation on human body shapes and emotional fashion themes Fuzzy cognitive maps fuzzy decision trees fuzzy relations composition human perception-based fashion recommender system personalized garment design
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Signal Processing Human Factors and Ergonomics Control and Systems Engineering Computer Networks and Communications Human-Computer Interaction Computer Science Applications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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