Organizing Resources on Tagging Systems using T-ORG
Published in In the proceedings of Proceedings of Workshop on Bridging the Gap between Semantic Web and Web 2.0 at European Semantic Web Conference 2007, 2007
Recommended citation: Rabeeh Abbasi, Steffen Staab, Philipp Cimiano, "Organizing Resources on Tagging Systems using T-ORG." In the proceedings of Proceedings of Workshop on Bridging the Gap between Semantic Web and Web 2.0 at European Semantic Web Conference 2007, 2007. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.175.1506
Tagging systems (or folksonomies) like Flickr or Delicious are expanding tremendously. More and more resources are being added to them. As the resources present on these system increase in amount, it becomes difficult to explore these resources. For this purpose, we present a system T-ORG, which provides a mechanism to organize these resources by classifying the tags (or keywords) attached to them into predefined categories. Supervised classification in this case seems infeasible; therefore we also propose a new classification algorithm T-KNOW that does not require training data. For our experiments, we have downloaded images and their tags from groups present on Flickr website and then classified these tags into different categories. We have used Cohen’s Kappa and F-measure to evaluate the classification results of T-KNOW. Results are encouraging and show that T-ORG can be used to explore resources in an effective manner.