Passage feedback with IRIS

Abstract

We compare a user-defined passage feedback (pf) system to a document feedback (df) system. Df employed the adaptive linear model for retrieval, while pf used weighted query expansion based on positive and negative feedback. Twenty-four searchers performed the same six tasks in varying search and system-order per TREC-8 guidelines. We hypothesized that pf, which featured interactive query expansion, would outperform df, which relied on automatic query expansion. Initial analysis appeared to reject this hypothesis, as df showed slightly higher overall performance than pf. However, analysis by system-order groups indicates only the first pf use had lower performance. These data suggest that pf was more difficult to learn than df, though the second pf use yielded competitive performance. If performance of pf is indeed affected by learning, an improved pf system with usability enhancements may prove to be an effective mechanism for interactive information retrieval.