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Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
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In this paper, we identify a fundamental algorithmic problem that we term succinct dynamic covering (SDC), arising in many modern-day web applications, including ad-serving and online recommendation systems such as in eBay, Netflix, and Amazon. Roughly speaking, SDC applies two restrictions to the well-studied Max-Coverage problem [14]: Given an integer k, X={1,2,...,n}and I={S_1,...,S_m}, S_i subseteq X, find |J| subseteq I, such that |J| We present algorithms and complexity results for coverage oracles. We present deterministic and probabilistic near-tight upper and lower bounds on the approximation ratio of SDC as a function of the amount of space available to the oracle. Our lower bound results show that to obtain constant-factor approximations we need Omega(mn) space. Fortunately, our upper bounds present an explicit tradeoff between space and approximation ratio, allowing us to determine the amount of space needed to guarantee certain accuracy.