Abstract
The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. Recently, different applications based on this vision have been designed, e.g. in the fields of knowledge management, community web portals, e-learning, multimedia retrieval, etc. It is obvious that the complex metadata descriptions generated on the basis of pre-defined ontologies serve as perfect input data for machine learning techniques. In this paper we propose an approach for clustering ontology-based metadata. Main contributions of this paper are the definition of a set of similarity measures for comparing ontology-based metadata and an application study using these measures within a hierarchical clustering algorithm.
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References
G. Bisson. Why and how to define a similarity measure for object based representation systems, 1995.
A. Delteil, C. Faron-Zucker, and R. Dieng. Learning ontologies from RDF annotations. In A. Maedche, S. Staab, C. Nedellec, and E. Hovy, editors, Proceedings of IJCAI-01 Workshop on Ontology Learning OL-2001, Seattle, August 2001, Menlo Park, 2001. AAAI Press.
W. Emde and D. Wettschereck. Relational instance-based learning. Proceedings of the 13th International Conference on Machine Learning, 1996, 1996.
T. R. Gruber. A translation approach to portable ontology specifications. Knowledge Acquisition, 6(2):199–221, 1993.
M. Kirsten and S. Wrobel. Relational distance-based clustering. pages 261–270. Proceedings of ILP-98, LNAI 1449, Springer, 1998, 1998.
I. V. Levenshtein. Binary Codes capable of correcting deletions, insertions, and reversals. Cybernetics and Control Theory, 10(8):707–710, 1966.
A. Maedche, S. Staab, N. Stojanovic, R. Studer, and Y. Sure. SEmantic PortAL — The SEAL approach. to appear in: Creating the Semantic Web. D. Fensel et al., MIT Press, MA, Cambridge, 2001.
C. D. Manning and H. Schuetze. Foundations of Statistical Natural Language Processing. MIT Press, Cambridge, Massachusetts, 1999.
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Maedche, A., Zacharias, V. (2002). Clustering Ontology-Based Metadata in the Semantic Web. In: Elomaa, T., Mannila, H., Toivonen, H. (eds) Principles of Data Mining and Knowledge Discovery. PKDD 2002. Lecture Notes in Computer Science, vol 2431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45681-3_29
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DOI: https://doi.org/10.1007/3-540-45681-3_29
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