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Visual Distinctive Language: Using a Hypertopic-Based Iconic Tagging System for Knowledge Sharing

Xiaoyue Ma 1 Jean-Pierre Cahier 1
1 Tech-CICO - TECHnologies pour la Coopération, l’Interaction et les COnnaissances dans les collectifs
ICD - Institut Charles Delaunay, CNRS - Centre National de la Recherche Scientifique : FRE2732
Abstract : Tagging systems for social semantic web 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 these textual tags to become less and less distinctive, making the use and reuse of tagging systems even harder. In this paper, we present an approach of Visual Distinctive Language to improve the representation of tags and their structure. This approach was also evaluated by a control experiment with an observation of tagging process, the results of which have validated our hypothesis.
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https://hal-utt.archives-ouvertes.fr/hal-02938042
Contributor : Jean-Baptiste Vu Van <>
Submitted on : Monday, September 14, 2020 - 4:20:01 PM
Last modification on : Wednesday, October 14, 2020 - 4:14:41 AM

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Xiaoyue Ma, Jean-Pierre Cahier. Visual Distinctive Language: Using a Hypertopic-Based Iconic Tagging System for Knowledge Sharing. 2012 IEEE 21st International Workshop On Enabling Technologies: Infrastructure For Collaborative Enterprises (WETICE), Jun 2012, Toulouse, France. pp.456-461, ⟨10.1109/WETICE.2012.54⟩. ⟨hal-02938042⟩

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