在有偏差的情况下最大化子模函数进行推荐（英文版）

英文标题：Maximizing Submodular Functions for Recommendation in the Presence of Biases中文摘要：本研究提出一种算法用于在考虑限制因素的情况下，最大化一类亚模模函数。算法能够保证在该模函数家族下，输出子集的效用最优，并均衡代表每个子集组。英文摘要：Subset selection tasks, arise in recommendation systems and search enginesand ask to select a subset of items that maximize the value for the user. Thevalues of subsets often display diminishing returns, and hence, submodularfunctions have been used to model them. If the inputs defining the submodularfunction are known, then existing al