Wong Pei Voon
ABSTRACT
Collaborative tagging applications or folksonomies allow internet users to annotate resources with personalized tags. However, freedom afforded users come at a cost: an uncontrolled vocabulary can result in tag ambiguity hindering navigation. Ambiguity can mislead users as they search for relevant resources. Recommenders that avoid ambiguous tags may be penalized by standard utility metrics for not promoting such tags.
To provide effectiveness of tag recommendation in term of accuracy and coverage, we propose a new method for tag recommendation approach based on social semantic web to overcome ambiguity and presenting users tags and resources that correspond more closely. This method is a combination of semantic content analysis methods and social network analysis methods.
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Index Terms
- A tag recommendation approach based on social semantic web
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