Similarity caching
Flavio Chierichetti, Ravi Kumar, Sergei Vassilvitskii · 2009
We introduce the similarity caching problem, a variant of classical caching in which an algorithm can return an element from the cache that is similar, but not necessarily identical, to the query element. We are motivated by buffer management questions in approximate nearest-neighbor applications, especially in the context of caching targeted advertisements on the web. Formally, we assume the queries lie in a metric space, with distance function d(.,.). A query p is considered a cache hit if there is a point q in the cache that is sufficiently close to p, i.e., for a threshold radius r, we have d(p,q) ≤ r. The goal is then to minimize the number of cache misses, vis-à-vis the optimal algorithm. As with classical caching, we use the competitive ratio to measure the performance of different algorithms.