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Learning to Reinforce Search Effectiveness
2015
Proceedings of the 2015 International Conference on Theory of Information Retrieval - ICTIR '15
Session search is an Information Retrieval (IR) task which handles a series of queries issued for a search task. In this paper, we propose a novel reinforcement learning style information retrieval framework and develop a new feedback learning algorithm to model user feedback, including clicks and query reformulations, as reinforcement signals and to generate rewards in the RL framework. From a new perspective, we view session search as a cooperative game played between two agents, the user and
doi:10.1145/2808194.2809468
dblp:conf/ictir/LuoDY15a
fatcat:7ui67ulsojhmpo6v4ipfotunwq