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Multimedia Tools and Applications

, Volume 69, Issue 3, pp 991–1019 | Cite as

Multimodal retrieval with relevance feedback based on genetic programming

  • Rodrigo Tripodi CalumbyEmail author
  • Ricardo da Silva Torres
  • Marcos André Gonçalves
Article

Abstract

This paper presents a framework for multimodal retrieval with relevance feedback based on genetic programming. In this supervised learning-to-rank framework, genetic programming is used for the discovery of effective combination functions of (multimodal) similarity measures using the information obtained throughout the user relevance feedback iterations. With these new functions, several similarity measures, including those extracted from different modalities (e.g., text, and content), are combined into one single measure that properly encodes the user preferences. This framework was instantiated for multimodal image retrieval using visual and textual features and was validated using two image collections, one from the Washington University and another from the ImageCLEF Photographic Retrieval Task. For this image retrieval instance several multimodal relevance feedback techniques were implemented and evaluated. The proposed approach has produced statistically significant better results for multimodal retrieval over single modality approaches and superior effectiveness when compared to the best submissions of the ImageCLEF Photographic Retrieval Task 2008.

Keywords

Multimodal retrieval Learn to rank Image retrieval Relevance feedback Genetic programming 

Notes

Acknowledgements

We would like to thank all partners from LIS (Laboratory of Information Systems - IC/UNICAMP), RECOD (Reasoning for Complex Data - IC/UNICAMP), LDB (Databases Lab - DCC/UFMG). This work was supported by The National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Level Personnel (CAPES), São Paulo Research Foundation (FAPESP), and Minas Gerais Agency for Research and Development (FAPEMIG).

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Rodrigo Tripodi Calumby
    • 1
    • 2
    Email author
  • Ricardo da Silva Torres
    • 2
  • Marcos André Gonçalves
    • 3
  1. 1.Department of Exact SciencesUniversity of Feira de SantanaFeira de SantanaBrazil
  2. 2.RECOD Lab, Institute of ComputingUniversity of CampinasCampinasBrazil
  3. 3.Department of Computer ScienceFederal University of Minas GeraisBelo HorizonteBrazil

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