Learning a semantic space from user's relevance feedback for image retrieval

@article{He2003LearningAS,
  title={Learning a semantic space from user's relevance feedback for image retrieval},
  author={Xiaofei He and Oliver King and Wei-Ying Ma and Mingjing Li and HongJiang Zhang},
  journal={IEEE Trans. Circuits Syst. Video Techn.},
  year={2003},
  volume={13},
  pages={39-48}
}
As current methods for content-based retrieval are incapable of capturing the semantics of images, we experiment with using spectral methods to infer a semantic space from user's relevance feedback, so that our system will gradually improve its retrieval performance through accumulated user interactions. In addition to the long-term learning process, we also model the traditional approaches to query refinement using relevance feedback as a short-term learning process. The proposed short- and… CONTINUE READING

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