Image-Based Fashion Recommendation with Attention to Users' Interests

Author:

Yao Wenxin1ORCID,Uchida Kaoru2ORCID,Zou Jianpeng1ORCID,Zhong Xiaolin3ORCID

Affiliation:

1. School of Software Engineering, University of Science and Technology of China, China and Graduate School of Computer and Information Sciences, Hosei University, Japan

2. Graduate School of Computer and Information Sciences, Hosei university, Japan

3. Meituan, China

Funder

JSPS Grands-in-Aid for Scientific Research (KAKENHI)

Publisher

ACM

Reference24 articles.

1. Apparel Goods Recommender System Based on Image Shape Features Extracted by a CNN

2. Adomavicius , G. , & Tuzhilin , A. ( 2005 ). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions . IEEE transactions on knowledge and data engineering, 17(6), 734-749. Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE transactions on knowledge and data engineering, 17(6), 734-749.

3. Recommender Systems

4. Deep Interest Network for Click-Through Rate Prediction

5. Zhou , G. , Mou , N. , Fan , Y. , Pi , Q. , Bian , W. , Zhou , C. , ... & Gai , K. ( 2019 , July). Deep interest evolution network for click-through rate prediction . In Proceedings of the AAAI conference on artificial intelligence (Vol. 33 , No. 01, pp. 5941 - 5948 ). Zhou, G., Mou, N., Fan, Y., Pi, Q., Bian, W., Zhou, C., ... & Gai, K. (2019, July). Deep interest evolution network for click-through rate prediction. In Proceedings of the AAAI conference on artificial intelligence (Vol. 33, No. 01, pp. 5941-5948).

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