Condensed List Relevance Models

Abstract

Pseudo-relevance feedback has traditionally been implemented as an expensive re-retrieval of documents from the target corpus. In this work, we demonstrate that, for high precision metrics, re-ranking the original feedback set provides nearly identical performance to re-retrieval with significantly lower latency.