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An Image Retrieval Method Based on Information Filtering of User Relevance Feedback Records

  • Xiangdong Zhou
  • Qi Zhang
  • Li Liu
  • Ailin Deng
  • Liang Zhang
  • Baile Shi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2762)

Abstract

This paper presents a composite image retrieval approach based on the analysis of the accumulated user relevance feedback records. To improve efficiency, semi-supervised fuzzy clustering is employed to classify the RF records, and the subsequent information filtering within the target cluster is performed to guide the refinement of query parameters. During information filtering, both the user’s relevance evaluations and the corresponding query images of the records are used to predict the semantic correlation between the database images and the current retrieval. Experiment results show that our method outperforms the traditional ones in both efficiency and effectiveness.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Xiangdong Zhou
    • 1
  • Qi Zhang
    • 1
  • Li Liu
    • 1
  • Ailin Deng
    • 1
  • Liang Zhang
    • 1
  • Baile Shi
    • 1
  1. 1.Department of Computing and Information TechnologyFudan UniversityShanghaiChina

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