Organizing Resources on Tagging Systems using T-ORG
R. Abbasi, S. Staab, and P. Cimiano. In proceedings of Workshop on Bridging the Gap between Semantic Web and Web 2.0 at ESWC 2007, page 97-110. (2007)
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.