ECIR 2012 Poster: Learning to Rank from Relevance Feedback for eDiscovery

Today I will be presenting a poster at ECIR 2012 about a paper Katja Hofmann and I have written.  The abstract and full paper are included below.

In recall-oriented search tasks retrieval systems are privy to a greater amount of user feedback. In this paper we present a novel method of combining relevance feedback with learning to rank. Our experiments use data from the 2010 TREC Legal track to demonstrate that learning to rank can tune relevance feedback to improve result rankings for specific queries, even with limited amounts of user feedback.

P. Lubell-Doughtie and K. Hofmann, "Learning to Rank from Relevance Feedback for e-Discovery," in ECIR, 2012.