The success of the Semantic Web depends on the availability of ontologies as well as on the proliferation of web pages annotated with metadata conforming to these ontologies. Thus, a crucial question is where to acquire these metadata. In this paper we propose PANKOW (Pattern-based Annotation through Knowledge on the Web), a method which employs an unsupervised, pattern-based approach to categorize instances with regard to an ontology. The approach is evaluated against the manual annotations of two human subjects. The approach is implemented in OntoMat, an annotation tool for the Semantic Web and shows very promising results.
Later, Cimiano et al. REF propose PANKOW, a novel approach towards the Self-Annotating Web, which employs an unsupervised, pattern-based approach to categorize instances with regard to a given ontology.
Towards the self-annotating web
WWW '04
Computer Science