Recommendation of complementary garments using ontology

This paper proposes a novel recommendation engine to suggest coordinated outfits to the users that complements each other. The proposed recommendation model encodes subjective knowledge of clothing experts in Multimedia Web Ontology Language (MOWL) and makes use of evidential and causal reasoning scheme to deal with the media properties of concepts. Our approach automatically identifies the user visual personality and interprets the contextual meaning of media features of the garments in the context of input query image. As a result, personalized complementary garments based on occasion of wear are recommended to the user. We have validated our approach with garment preferences of various models with a large collection of shirts and trousers, collected from various websites.