Tractable near-optimal policies for crawling
Yossi Azar, Eric Horvitz, Eyal Lubetzky, Yuval Peres, Dafna Shahaf · Proceedings of the National Academy of Sciences · 2018
Significance We present a tractable algorithm that provides a near-optimal solution to the crawling problem, a fundamental challenge at the heart of web search: Given a large quantity of distributed and dynamic web content, what pages do we choose to update a local cache with the goal of serving up-to-date pages to client requests? Solving this optimization requires identifying the best set of pages to refresh given popularity rates and change rates—an intractable problem in the general case. To overcome this intractability, we show that the optimal randomized strategy can be efficiently determined (in near-linear time) and then use it to produce a deterministic policy that exhibits excellent performance in experiments.