Social bookmarking systems and their emergent information structures, known as folksonomies, are increasingly important data sources for Semantic Web applications. A key question for harvesting semantics from these systems is how to extend and adapt traditional notions of similarity to folksonomies, and which measures are best suited for applications such as navigation support, semantic search, and ontology learning. Here we build an evaluation framework to compare various general folksonomy-based similarity measures derived from established information-theoretic, statistical, and practical measures. Our framework deals generally and symmetrically with users, tags, and resources. For evaluation purposes we focus on similarity among tags and resources, considering different ways to aggregate annotations across users. After comparing how tag similarity measures predict user-created tag relations, we provide an external grounding by user-validated semantic proxies based on WordNet and the Open Directory. We also investigate the issue of scalability. We find that mutual information with distributional micro-aggregation across users yields the highest accuracy, but is not scalable; per-user projection with collaborative aggregation provides the best scalable approach via incremental computations. The results are consistent across resource and tag similarity.
Social bookmarking systems and their emergent information structures, known as folksonomies, are increasingly important data sources for Semantic Web applications. A key question for harvesting semantics from these systems is how to extend and adapt traditional notions of similarity to folksonomies, and which measures are best suited for applications such as navigation support, semantic search, and ontology learning. Here we build an evaluation framework to compare various general folksonomy-based similarity measures derived from established information-theoretic, statistical, and practical measures. Our framework deals generally and symmetrically with users, tags, and resources. For evaluation purposes we focus on similarity among tags and resources, considering different ways to aggregate annotations across users. After comparing how tag similarity measures predict user-created tag relations, we provide an external grounding by user-validated semantic proxies based on WordNet and the Open Directory. We also investigate the issue of scalability. We find that mutual information with distributional micro-aggregation across users yields the highest accuracy, but is not scalable; per-user projection with collaborative aggregation provides the best scalable approach via incremental computations. The results are consistent across resource and tag similarity.
B. Klein, S. Lau, A. Pirali, T. Löffler, and K. David. ASWN '08: Proceedings of the 2008 Eighth International Workshop on Applications and Services in Wireless Networks, page 20--25. Washington, DC, USA, IEEE Computer Society, (2008)
G. Stumme. Proc. 3rd Intl. Conf. on Formal Concept Analysis, volume 3403 of Lecture Notes in Computer Science, page 315-328. Heidelberg, Springer, (2005)
C. Schmitz, A. Hotho, R. Jäschke, and G. Stumme. The Semantic Web: Research and Applications, volume 4011 of LNAI, page 530-544. Heidelberg, Springer, (2006)
R. Jäschke, A. Hotho, C. Schmitz, and G. Stumme. Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007), volume 4604 of Lecture Notes in Artificial Intelligence, page 283--295. Berlin, Heidelberg, Springer-Verlag, (July 2007)
M. Grahl, A. Hotho, and G. Stumme. 7th International Conference on Knowledge Management (I-KNOW '07), page 356-364. Graz, Austria, Know-Center, (September 2007)
M. Atzmueller, D. Benz, A. Hotho, and G. Stumme (Eds.) Technical report (KIS), 2010-10 Department of Electrical Engineering/Computer Science, Kassel University, (2010)
D. Benz, B. Krause, G. Kumar, A. Hotho, and G. Stumme. Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009), Bled, Slovenia, (September 2009)
C. Cattuto, D. Benz, A. Hotho, and G. Stumme. The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008, volume 5318 of LNAI, page 615--631. Heidelberg, Springer, (2008)
M. Atzmueller, S. Beer, and F. Puppe. Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources, IGI Global, (2012)