thomsonreuters.com

Work on using relevance feedback for retrieval has focused on the single retrieved list setting. That is, an initial docu-ment list is retrieved in response to the query and feedback for the most highly ranked documents is used to perform a second search. We address a setting wherein the list for which feedback is provided results from fusing several in-termediate retrieved lists. Accordingly, we devise methods that utilize the feedback while exploiting the special char-acteristics of the fusion setting. Specifically, the feedback serves two different, yet complementary, purposes. The first is to directly rank the pool of documents in the interme-diate lists. The second is to estimate the effectiveness of the intermediate lists for improved re-fusion. In addition, we present a meta fusion method that uses the feedback for these two purposes simultaneously. Empirical evaluation demonstrates the merits of our approach. As a case in point, the retrieval performance is substantially better than that of using the relevance feedback as in the single list setting. The performance also substantially transcends that of a pre-viously proposed approach to utilizing relevance feedback in fusion-based retrieval