Learning to rank for web image retrieval based on genetic programming

@article{Piji2009LearningTR,
  title={Learning to rank for web image retrieval based on genetic programming},
  author={Li Piji and Ma Jun},
  journal={2009 2nd IEEE International Conference on Broadband Network & Multimedia Technology},
  year={2009},
  pages={137-142}
}
  • Li Piji, Ma Jun
  • Published 2009 in
    2009 2nd IEEE International Conference on…
Ranking is a crucial task in information retrieval systems. This paper proposes a novel ranking model named WIRank, which employs a layered genetic programming architecture to automatically generate an effective ranking function, by combining various types of evidences in web image retrieval, including text information, image-based features and link structure analysis. This paper also introduces a new significant feature to represent images: Temporal Information, which is rarely utilized in the… CONTINUE READING

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