Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published February 2011 | metadata_only
Book Section - Chapter

Dynamic Ranked Retrieval


We present a theoretically well-founded retrieval model for dynamically generating rankings based on interactive user feedback. Unlike conventional rankings that remain static after the query was issued, dynamic rankings allow and anticipate user activity, thus providing a way to combine the otherwise contradictory goals of result diversification and high recall. We develop a decision-theoretic framework to guide the design and evaluation of algorithms for this interactive retrieval setting. Furthermore, we propose two dynamic ranking algorithms, both of which are computationally efficient. We prove that these algorithms provide retrieval performance that is guaranteed to be at least as good as the optimal static ranking algorithm. In empirical evaluations, dynamic ranking shows substantial improvements in retrieval performance over conventional static rankings.

Additional Information

© 2011 ACM. This work was funded in part by NSF Award IIS-0905467. The third author was also funded in part by a Microsoft Research Graduate Fellowship. The authors thank Robert Kleinberg for valuable discussions regarding this work.

Additional details

August 19, 2023
August 19, 2023