IJSEA Volume 13 Issue 3

Personalized Clothing Recommendation System Based on Customer Preference

Mengjiao Yuan, Zhiming Hu
10.7753/IJSEA1303.1002
keywords : Preference; Clothing personalization; Springboot; Collaborative Filtering recommendation algorithm

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Nowadays,with the rapid development of the Internet,online shopping is becoming more and more convenient. At present,the income of online shopping is far more than that of offline physical stores. A good clothing recommendation system can help sellers sell clothes better and buyers choose suitable clothes faster. This paper firstly describes the big data technology. Then,it introduces the advantages of using springboot technology and big data analysis,and focuses on the collaborative filtering recommendation algorithm used in this paper. Finally,the personalized clothing recommendation system is realized through these technologies. The system can use the identity of user,stylist and administrator to log in,and provide functions such as comments and clothing collocation,and establish a clothing forum for information release and exchange. According to the test results,the system can basically meet the needs of most users,and the system security and performance are also ideal.
@artical{m1332024ijsea13031002,
Title = "Personalized Clothing Recommendation System Based on Customer Preference",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "13",
Issue ="3",
Pages ="5 - 8",
Year = "2024",
Authors ="Mengjiao Yuan, Zhiming Hu"}