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Système participatif de tags iconiques basé sur un langage visuel instinctif multi-points de vue

Abstract : Tags systems for Knowledge Organization System centralize and provide the tags that can be employed in classifying, sharing and seeking knowledge on the web for personal or organizational use. However, an increased variety of vocabularies and languages cause connections between tags and documents marked by textual tags to become less and less distinctive, making the use and reuse of tags systems even harder. Although previous attempts have been made onto visual tags system by using icons, it caused the disorientation when users facing with plant of isolated symbols. Our research dedicates to searching a new approach to improve the representation of tags and their structure in a tags system, where well-structured icons enhance the tagging effectiveness by considering tagging quality and tagging speed. The LVD (Visual Distinctive Language)-based iconic tags system is proposed and presented in this thesis to bring amelioration mainly from semiotic interpretation of tag meaning and graphical code of tag structure. The arrangement of icons is as well another interesting topic that was deal with in our research to offers a more complete definition of iconic tags system. Apart from modeling and evaluating the LVD-based iconic tags system we have considered the way to build up such icon system in today’s cooperative knowledge sharing context and made it possible to manage and share iconic tags on a collaborative plate-form
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  • HAL Id : tel-02965683, version 1

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Xiaoyue Ma. Système participatif de tags iconiques basé sur un langage visuel instinctif multi-points de vue. Web. Université de Technologie de Troyes, 2013. Français. ⟨NNT : 2013TROY0009⟩. ⟨tel-02965683⟩

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