Abstract
Internet shopping has become a major consumer channel, but the lack of professional knowledge in clothing matching and the inability to try on clothes often lead to blind consumption and high clothing return rates. Based on the experience of senior clothing experts, a digital clothing tagging system was established, the weight of clothing matching was quantified, and customer image parameters were designed to create a clothing recommendation system for dress matching based on a knowledge graph. According to the system testing results, it can be concluded that the system can meet the needs of at least 2000 users simultaneously, and the recommended response time should not exceed 1.5 s.
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Tao, Q., Wang, J., Chen, C., Zhu, S., Shi, Y. (2023). Expert Knowledge-Driven Clothing Matching Recommendation System. In: Huang, DS., Premaratne, P., Jin, B., Qu, B., Jo, KH., Hussain, A. (eds) Advanced Intelligent Computing Technology and Applications. ICIC 2023. Lecture Notes in Computer Science(), vol 14090. Springer, Singapore. https://doi.org/10.1007/978-981-99-4761-4_48
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DOI: https://doi.org/10.1007/978-981-99-4761-4_48
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