• DocumentCode
    1868272
  • Title

    Are Clickthroughs Useful for Image Labelling?

  • Author

    Ashman, Helen ; Antunovic, Michael ; Donner, Christoph ; Frith, Rebecca ; Rebelos, Eric ; Schmakeit, Jan-Felix ; Smith, Gavin ; Truran, Mark

  • Volume
    1
  • fYear
    2009
  • fDate
    15-18 Sept. 2009
  • Firstpage
    191
  • Lastpage
    197
  • Abstract
    In this paper we look at how images can be labelled as a result of click throughs from searches. One approach acts as a filter on image searches specifically, while the other approach propagates labels to images from their containing pages, where those pages were labelled themselves using clickthrough as a filter on text search. Then the paper reports on an experiment where users ranked for relevance six methods for labelling images, comparing the two clickthrough-based methods with flickr´s amateur explicit labelling, Getty´s professional explicit labelling, Google´s standard image search, and the new Google Image Labeller. As well as comparing the accuracy of the proposed image labelling methods and discovering that automatic methods outperform explicit human labelling methods, the experiment suggests clickthrough data is reliable with very few clicks for image classification purposes.
  • Keywords
    Australia; Conferences; Electronic mail; Filters; Humans; Image classification; Information science; Intelligent agent; Labeling; Search engines;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09. IEEE/WIC/ACM International Joint Conferences on
  • Conference_Location
    Milan, Italy
  • Print_ISBN
    978-0-7695-3801-3
  • Electronic_ISBN
    978-1-4244-5331-3
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2009.35
  • Filename
    5286074