Abstract
In this paper, we introduce an approach for clothing personalized recommendation system that is able to recommend clothing items to women, according to their fashion styles and body types. Thus, our recommendation approach includes three main modules: one for automatically identifying the fashion style, the other for detecting body type, and the third is responsible for recommending clothing categories with models linked to clothing images. Thus, it allows the women to select appropriate clothing options, considering clothing categories that include: dresses, coats, tops, sweaters, jackets. We have evaluated our recommendation approach and preliminary results indicate that it significantly supports the users with adequate clothing choices.
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de Barros Costa, E., Rocha, H.J.B., Silva, E.T., Lima, N.C., Cavalcanti, J. (2017). Understanding and Personalising Clothing Recommendation for Women. In: Rocha, Á., Correia, A., Adeli, H., Reis, L., Costanzo, S. (eds) Recent Advances in Information Systems and Technologies. WorldCIST 2017. Advances in Intelligent Systems and Computing, vol 569. Springer, Cham. https://doi.org/10.1007/978-3-319-56535-4_82
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DOI: https://doi.org/10.1007/978-3-319-56535-4_82
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