IRIS at TREC-8
Kiduk Yang, Kelly L. Maglaughlin · Text REtrieval Conference · 1999
We tested two relevance feedback models, an adaptive linear model and a probabilistic model, using massive feedback query expansion in TREC-5 (Sumner & Shaw, 1997), experimented with a three-valued scale of relevance and reduced feedback query expansion in TREC-6 (Sumner, Yang, Akers & Shaw, 1998), and examined the effectiveness of relevance feedback using a subcollection and the effect of system features in an interactive retrieval system called IRIS (Information Retrieval Interactive System) in TREC-7 (Yang, Maglaughlin, Mehol & Sumner, 1999). In TREC-8, we continued our exploration of relevance feedback approaches. Based on the result of our TREC-7 interactive experiment, which suggested relevance feedback using user-selected passages to be an effective alternative to conventional document feedback, our TREC-8 interactive experiment compared a passage feedback system and a document feedback system that were identical in all aspects except for the feedback mechanism. For the TREC-8 ad-hoc task, we merged results of pseudo-relevance feedback to subcollections as in TREC-7. Our results were consistent with that of TREC-7. The results of passage feedback, whose system log showed high level of searcher intervention, was superior to the document feedback results. As in TREC-7, our ad-hoc results showed high precision in top few documents, but performed poorly overall compared to results using the collection as a whole.