Incremental relevance feedback for information filtering

We use data from the TREC routing experiments to explore how relevance feedback can be applied incrementally-using a few judged documents each tim~to achieve results that are as good as if the feedback occurred in one paas. We show that relatively few judgments are needed to get highquality results. We also demonstrate methods that reduce the amount of information archived from past judged documents without adversely tiecting effectiveness. A novel simulation shows that such techniques are useful for handling long-standing queries with drifting notions of relevance.