A Comparative Study of Diversity Methods for Hybrid Text and Image Retrieval Approaches View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2009

AUTHORS

Sabrina Tollari , Philippe Mulhem , Marin Ferecatu , Hervé Glotin , Marcin Detyniecki , Patrick Gallinari , Hichem Sahbi , Zhong-Qiu Zhao

ABSTRACT

This article compares eight different diversity methods: 3 based on visual information, 1 based on date information, 3 adapted to each topic based on location and visual information; finally, for completeness, 1 based on random permutation. To compare the effectiveness of these methods, we apply them on 26 runs obtained with varied methods from different research teams and based on different modalities. We then discuss the results of the more than 200 obtained runs. The results show that query-adapted methods are more efficient than non-adapted method, that visual only runs are more difficult to diversify than text only and text-image runs, and finally that only few methods maximize both the precision and the cluster recall at 20 documents. More... »

PAGES

585-592

References to SciGraph publications

  • 2009. LIG at ImageCLEF 2008 in EVALUATING SYSTEMS FOR MULTILINGUAL AND MULTIMODAL INFORMATION ACCESS
  • 2009. Overview of the ImageCLEFphoto 2008 Photographic Retrieval Task in EVALUATING SYSTEMS FOR MULTILINGUAL AND MULTIMODAL INFORMATION ACCESS
  • 2009. Visual Affinity Propagation Improves Sub-topics Diversity without Loss of Precision in Web Photo Retrieval in EVALUATING SYSTEMS FOR MULTILINGUAL AND MULTIMODAL INFORMATION ACCESS
  • 2009. Using Visual Concepts and Fast Visual Diversity to Improve Image Retrieval in EVALUATING SYSTEMS FOR MULTILINGUAL AND MULTIMODAL INFORMATION ACCESS
  • Book

    TITLE

    Evaluating Systems for Multilingual and Multimodal Information Access

    ISBN

    978-3-642-04446-5
    978-3-642-04447-2

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-04447-2_72

    DOI

    http://dx.doi.org/10.1007/978-3-642-04447-2_72

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1052833888


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