Museums have large databases of images. The librarians that are using these databases are doing two types of images search: either they know what they are looking for in the database (a specific image or a specific set of well defined images such as kings of France), or they do not know precisely what they are looking for (e.g., when they are required to build images portfolios about some concepts such as “decency”). As each image is having a number of metadata, searching for a well-defined image, or for set of images, is easily solved. On the contrary, this is a hard problem when the task is to illustrate a given concept such as “freedom”, “decency”, “bread”, or “transparency” since these concepts are not metadata. How to find images that are somewhat analogs because they illustrate a given concept?

We collected and analyzed the search results of librarians that were given themselves the task of finding images related to a given concept. Seven relations between the concept and the images were found as explanation of the selection of images for any concept: conceptual property, causality, effectivity semantic, anti-logic, metaphorical-vehicle and metaphorical-topic. The inter-rate agreement of independent judges that evaluated the relations was of .78.

Finally, we designed an experiment to evaluate how much metaphor in images can be understandable.


Search Engine Specific Image Image Search Navigation Data Bread Making 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Charles Candau
    • 1
  • Geoffrey Ventalon
    • 1
  • Javier Barcenilla
    • 1
  • Charles Tijus
    • 1
  1. 1.Laboratory Cognitions Humaine et ArtificielleUniversity Paris 8France

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