Ranked Document Selection

Ian Munro, Gonzalo Navarro, and Sharma Thankachan

Let D be a collection of string documents of n characters in total. The top-k document retrieval problem} is to preprocess D into a data structure that, given a query (P,k), can return the k documents of D most relevant to pattern P. The relevance of a document d for a pattern P is given by a predefined ranking function w(P,d). Linear space and optimal query time solutions already exist for this problem. In this paper we consider a novel problem, document selection, in which a query (P,k) aims to report the kth document most relevant to P (instead of reporting all top-k documents). We present a data structure using O(n log^e n) space, for any constant e > 0, answering selection queries in time O(log k / log log n), and a linear-space data structure answering queries in time O(log k), given the locus node of P in a (generalized) suffix tree of D. We also prove that it is unlikely that a succinct-space solution for this problem exists with poly-logarithmic query time, and that O(log k / log log n) is indeed optimal within O(n polylog n) space for most text families. Finally, we present some additional space-time trade-offs exploring the extremes of those lower bounds.