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Reinforcement learning for combining relevance feedback techniques
Proceedings Ninth IEEE International Conference on Computer Vision
Relevance feedback (RF) is an interactive process which refines the retrievals by utilizing user's feedback history. Most researchers strive to develop new RF techniques and ignore the advantages of existing ones. In this paper, we propose an image relevance reinforcement learning (IRRL) model for integrating existing RF techniques. Various integration schemes are presented and a long-term shared memory is used to exploit the retrieval experience from multiple users. Also, a concept digestingdoi:10.1109/iccv.2003.1238390 dblp:conf/iccv/YinBCD03 fatcat:mtsn24yv2vgyxa3chv4pvyc57a