Learning to rank for web image retrieval based on genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Li:2009:ieeeIC-BNMT,
  author =       "Piji Li and Jun Ma",
  title =        "Learning to rank for web image retrieval based on
                 genetic programming",
  booktitle =    "2nd IEEE International Conference on Broadband Network
                 Multimedia Technology, IC-BNMT '09",
  year =         "2009",
  month =        oct,
  pages =        "137--142",
  keywords =     "genetic algorithms, genetic programming, WIRank, Web
                 image retrieval, graph theory, image-based feature,
                 information retrieval system, link structure analysis,
                 ranking, temporal information, text information,
                 Internet, graph theory, image retrieval, text
                 analysis",
  DOI =          "doi:10.1109/ICBNMT.2009.5348465",
  abstract =     "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 used in the current information
                 retrieval systems and applications. The experimental
                 results show that the proposed algorithms are capable
                 of learning effective ranking functions for Web image
                 retrieval. Significant improvement in relevancy
                 obtained, in comparison to some other well-known
                 ranking techniques, in terms of MAP, NDCG@n and D@n.",
  notes =        "Also known as \cite{5348465}",
}

Genetic Programming entries for Piji Li Jun Ma

Citations