Reinforcement Learning to Rank with Pairwise Policy Gradient

SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval Virtual Event China July, 2020, pp. 509-518, 2020.

Cited by: 0|Bibtex|Views162|DOI:https://doi.org/10.1145/3397271.3401148
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Other Links: dl.acm.org|dblp.uni-trier.de|academic.microsoft.com

Abstract:

This paper concerns reinforcement learning~(RL) of the document ranking models for information retrieval~(IR). One branch of the RL approaches to ranking formalize the process of ranking with Markov decision process~(MDP) and determine the model parameters with policy gradient. Though preliminary success has been shown, these approaches a...More

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