Enhancing Factorization Machines with Generalized Metric Learning
IEEE Transactions on Knowledge and Data Engineering, pp. 1-1, 2020.
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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