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

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...

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Bibliographic Details
Published in2012 IEEE 21st International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises pp. 456 - 461
Main Authors Xiaoyue Ma, Cahier, J-P
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2012
Subjects
Analysis of variance
Hypertopic
icon
Image color analysis
Knowledge engineering
knowledge representation
Semantic Web
Shape
social semantic web
Tagging
tagging system
Visualization
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Summary: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.
ISBN:1467318884
9781467318884
ISSN:1524-4547
2641-8169
DOI:10.1109/WETICE.2012.54