ACoAR – A Method for the Automatic Classification of Annotated Resources – KCAP 2009


As the number of Web 2.0 sites increases, so do the use of folksonomies as classification systems. Their increasing popularity has made them interesting as a tool to bridge the gap between Web 2.0 and the Semantic Web. In this paper we propose a classification method that automatically classifies annotated resources under the concepts of a classification system represented by an ontology. We evaluate the method using information obtained from two well known systems used to classify web pages: i) for the folksonomy information and ii) DMOZ project for an existing ontology. Results obtained provide a correct classification rate of resources of 73%, rising to 93% when using an adequate threshold.


Francisco Echarte, José Javier Astrain, Alberto Córdoba, Jesús Villadangos and Aritz Labat


  • Classification results (CSV): download
  • Distances between classification concepts: download
  • Ontology modeling method components: download


Echarte, F., Astrain, J. J., Córdoba, A., Villadangos, J., and Labat, A. 2009. ACoAR: a method for the automatic classification of annotated resources. In Proceedings of the Fifth international Conference on Knowledge Capture (Redondo Beach, California, USA, September 01 – 04, 2009). K-CAP ’09. ACM, New York, NY, 181-182