Enhancing Factorization Machines with Generalized Metric Learning

Yangyang Guo
Yangyang Guo
Zhiyong Cheng
Zhiyong Cheng
Jiazheng Jing
Jiazheng Jing
Yanpeng Lin
Yanpeng Lin

IEEE Transactions on Knowledge and Data Engineering, pp. 1-1, 2020.

Cited by: 1|Bibtex|Views116|DOI:https://doi.org/10.1109/TKDE.2020.3034613
Other Links: arxiv.org|academic.microsoft.com

Abstract:

Factorization Machines (FMs) are effective in incorporating side information to overcome the cold-start and data sparsity problems in recommender systems. Traditional FMs adopt the inner product to model the second-order interactions between different attributes, which are represented via feature vectors. The problem is that the inner p...More

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