Clustering and Constructing User Coresets to Accelerate Large-scale Top-K Recommender Systems
WWW '20: The Web Conference 2020 Taipei Taiwan April, 2020, pp. 2177-2187, 2020.
Top-K recommender systems aim to generate few but satisfactory personalized recommendations for various practical applications, such as item recommendation for e-commerce and link prediction for social networks. However, the numbers of users and items can be enormous, thereby leading to myriad potential recommendations as well as the bott...More
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