Dynamic ranked retrieval

Christina Brandt, Thorsten Joachims, Yisong Yue, Jacob Bank
2011 Proceedings of the fourth ACM international conference on Web search and data mining - WSDM '11  
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.
more » ... thermore, 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.
doi:10.1145/1935826.1935872 dblp:conf/wsdm/BrandtJYB11 fatcat:phpoxftkijfczomdzb5q3jmole