Personalised Fashion Recommendation using Deep Learning

被引:3
|
作者
Sonie, Omprakash [1 ]
Chelliah, Muthusamy [1 ]
Sural, Shamik [2 ]
机构
[1] Flipkart, Bengaluru, India
[2] IIT Kharagpur, Kharagpur, W Bengal, India
来源
PROCEEDINGS OF THE 6TH ACM IKDD CODS AND 24TH COMAD | 2019年
关键词
Fashion recommendation; Deep learning; Data analytics;
D O I
10.1145/3297001.3297066
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Clothing we wear reveals our personal style - wealth, occupation, religion, location and socio-identity. Shopper's aesthetic preferences thus influence purchasing decision in a lifestyle marketplace. Given the image of a fashion item, recommending complementary matches is a challenge. This tutorial discusses various techniques for fashion recommendation which in turn enhance conventional data mining approaches like collaborative filtering and matrix factorization. For a few such models and methods, we outline results using real-world data from various online shopping platforms. Recent advances in deep learning are presented for compatibility modeling, learning-to-rank and explainable recommendation.
引用
收藏
页码:368 / 368
页数:1
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