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  • × author_ss:"Ménard, E."
  • × theme_ss:"Multilinguale Probleme"
  1. Ménard, E.; Khashman, N.; Kochkina, S.; Torres-Moreno, J.-M.; Velazquez-Morales, P.; Zhou, F.; Jourlin, P.; Rawat, P.; Peinl, P.; Linhares Pontes, E.; Brunetti., I.: ¬A second life for TIIARA : from bilingual to multilingual! (2016) 0.02 
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    Abstract
    Multilingual controlled vocabularies are rare and often very limited in the choice of languages offered. TIIARA (Taxonomy for Image Indexing and RetrievAl) is a bilingual taxonomy developed for image indexing and retrieval. This controlled vocabulary offers indexers and image searchers innovative and coherent access points for ordinary images. The preliminary steps of the elaboration of the bilingual structure are presented. For its initial development, TIIARA included only two languages, French and English. As a logical follow-up, TIIARA was translated into eight languages-Arabic, Spanish, Brazilian Portuguese, Mandarin Chinese, Italian, German, Hindi and Russian-in order to increase its international scope. This paper briefly describes the different stages of the development of the bilingual structure. The processes used in the translations are subsequently presented, as well as the main difficulties encountered by the translators. Adding more languages in TIIARA constitutes an added value for a controlled vocabulary meant to be used by image searchers, who are often limited by their lack of knowledge of multiple languages.
    Source
    Knowledge organization. 43(2016) no.1, S.22-34
    Type
    a
  2. Ménard, E.: Indexing and retrieving images in a multilingual world (2008) 0.00 
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    Content
    This paper presents the problem statement, the methodology and the preliminary results of a research project aiming to compare two different approaches for indexing images, namely: traditional image indexing with the use of controlled vocabularies, and free image indexing using uncontrolled vocabulary. The experiment intends to measure their respective performance for image retrieval in a multilingual context, in terms of effectiveness, efficiency, and satisfaction of the user.
    Type
    a
  3. Ménard, E.: Ordinary image retrieval in a multilingual context : a comparison of two indexing vocabularies (2010) 0.00 
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    Abstract
    Purpose - This paper seeks to examine image retrieval within two different contexts: a monolingual context where the language of the query is the same as the indexing language and a multilingual context where the language of the query is different from the indexing language. The study also aims to compare two different approaches for the indexing of ordinary images representing common objects: traditional image indexing with the use of a controlled vocabulary and free image indexing using uncontrolled vocabulary. Design/methodology/approach - This research uses three data collection methods. An analysis of the indexing terms was employed in order to examine the multiplicity of term types assigned to images. A simulation of the retrieval process involving a set of 30 images was performed with 60 participants. The quantification of the retrieval performance of each indexing approach was based on the usability measures, that is, effectiveness, efficiency and satisfaction of the user. Finally, a questionnaire was used to gather information on searcher satisfaction during and after the retrieval process. Findings - The results of this research are twofold. The analysis of indexing terms associated with all the 3,950 images provides a comprehensive description of the characteristics of the four non-combined indexing forms used for the study. Also, the retrieval simulation results offers information about the relative performance of the six indexing forms (combined and non-combined) in terms of their effectiveness, efficiency (temporal and human) and the image searcher's satisfaction. Originality/value - The findings of the study suggest that, in the near future, the information systems could benefit from allowing an increased coexistence of controlled vocabularies and uncontrolled vocabularies, resulting from collaborative image tagging, for example, and giving the users the possibility to dynamically participate in the image-indexing process, in a more user-centred way.
    Type
    a

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