Open AccessGarment knowledge base development based on fuzzy technology for recommendation system
Author(s) -
Junjie Zhang,
Xianyi Zeng,
Min Dong,
Weibo Li,
Hua Yuan
Publication year - 2020
Publication title -
industria textilă
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.281
H-Index - 14
ISSN - 1222-5347
DOI - 10.35530/it.071.05.1724
Subject(s) - knowledge base , base (topology) , product (mathematics) , fuzzy logic , knowledge based systems , computer science , clothing , knowledge management , order (exchange) , new product development , recommender system , artificial intelligence , machine learning , business , mathematics , marketing , mathematical analysis , geometry , archaeology , finance , history
With the rapid development of garments recommendation systems, more and more garment knowledge base have beenwidely developed. The research in this paper aims to build a garment knowledge base in order to help generalconsumers to identify the most relevant products satisfying their specific requirements. We design four experiments forbuilding this knowledge base by 8 pairs of normalized sensory evaluation criteria for describing both consumers’expectations and product profile. The theory of fuzzy composition technology is applied for setting up garmentknowledge base which can be used for consumer-oriented intelligent garment recommendation system. Compared withthe other knowledge base, this knowledge base is more robust and more interpretable owing to its capacity of handlingvague, imprecise, uncertain, or ambiguous.