LAUSR

Abstract With the rapid development of clothing online shopping, customers have a higher demand for more accurate clothing size recommendation systems. The work this paper presented is compatible with the four body types specified in the Chinese standard. Then, the subdivision was performed where each of the major body types corresponded to four characteristic indices. In addition, each characteristic index had three attributes. Therefore, the female body can be subdivided into 81 types for each major type. Subsequently, this paper suggests an improved clothing size recommendation system that considers subdivided body types. The recommendation criteria in the approach were refined by a pressure distribution analysis through a virtual fitting simulation. Finally, case studies were conducted on customers of body type A (accounting for 52.73% of bodies) to demonstrate the procedures of the proposed approach. Practitioner summary: This study proposes an improved clothing size recommendation approach based on the subdivision of code-specified female body types. Compared with existing clothing size recommendations, the proposed approach can help customers find formfitting sizes more accurately.