Deeper Semantics Goes a Long Way: Fuzzified Representation and Matching of Color Descriptions for Online Clothing Search

Indexing and retrieval by color descriptions are very important to finding certain web resources, which is typical in the example of online clothing search. However, both keyword matching and semantic mediation by the current ontologies may suffer from the semantic gap between the similarity evaluation and the human perception, which requests the exploitation of “deeper” semantics of color descriptions to reduce this gap. Considering the inherent variability and imprecision characterizing color naming, this paper proposes a novel approach to define (1) the fuzzy semantics of color names on the HSL color space together with their knowledge representation in fuzzy conceptual graphs, and (2) the associated measures to evaluate the similarity between fuzzified color descriptions. The experimental results rendered by the prototype clothing search system have preliminarily shown the strength of the deeper semantics surpassing the ability of both keywords and a concept hierarchy, in handling the matching problem of color descriptions in the targeted web resource search.