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. Krause, A. Hotho, and G. Stumme. Advances in Information Retrieval, 30th European Conference on IR Research, ECIR 2008, volume 4956 of LNAI, page 101-113. Heidelberg, Springer, (2008)
C. Schmitz, A. Hotho, R. Jäschke, and G. Stumme. Data Science and Classification: Proc. of the 10th IFCS Conf., page 261--270. Berlin, Heidelberg, Springer, (2006)
R. Jäschke, A. Hotho, C. Schmitz, B. Ganter, and G. Stumme. Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06), page 907-911. Hong Kong, IEEE Computer Society, (December 2006)
R. Jäschke, B. Krause, A. Hotho, and G. Stumme. Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008), AAAI Press, (2008)
S. Bleul, K. Geihs, D. Comes, and M. Kirchhoff. 16. Fachtagung Kommunikation in Verteilten Systemen, KiVS 2009, Kassel, Kassel, Germany, University of Kassel, VDE, (March 2009)
D. Comes, S. Bleul, and M. Zapf. Workshops der Wissenschaftlichen Konferenz Kommunikation in Verteilten Systemen (WowKiVS) 2009, Kassel, Kassel, Germany, University of Kassel, VDE, (2009)
R. Reichle, M. Wagner, M. Khan, K. Geihs, M. Valla, C. Fra, N. Paspallis, and G. Papadopoulos. 5th IEEE Workshop on Context Modeling and Reasoning (CoMoRea) in conjunction with the 6th IEEE International Conference on Pervasive Computing and Communication (PerCom), IEEE Computer Society Press, (2008)
T. Weise, S. Niemczyk, H. Skubch, R. Reichle, and K. Geihs. Proceedings of Genetic and Evolutionary Computation Conference, GECCO 2008, page 795--802. ACM Press, (July 2008)online version.
M. Khan, R. Reichle, and K. Geihs. IEEE Distributed Systems Online (DSOnline), 9 (7):
0807-o7001(July 2008)link. http://dsonline.computer.org/portal/pages/dsonline/2008/07/o7001.html.
M. Zapf, and T. Weise. The third International Workshop on Self-Organizing Systems (IWSOS'08), volume 5343 of Lecture Notes in Computer Science (LNCS), LNCS Sublibrary: SL 5 -- Computer Communication Networks and Telecommunications, page 299--304. Sprigner, (December 2008)online version.
T. Weise, M. Zapf, and K. Geihs. Genetic Programming - Proceedings of the 11th European Conference on Genetic Programming, EuroGP 2008, volume 4971/2008 of Lecture Notes in Computer Science (LNCS), Theoretical Computer Science and General Issues, page 254--265. Naples, Italy, Springer-Verlag GmbH, (March 2008)http://www.it-weise.de/documents/index.html#WZG2008DGPFa.
P. Baer, T. Weise, and K. Geihs. The Third International Conference on Systems and Networks Communications, IEEE Computer Society Press, (October 2008)
T. Weise, H. Skubch, M. Zapf, and K. Geihs. Kasseler Informatikschriften (KIS), 2008, 3. Distributed Systems Group, FB 16, University of Kassel, Wilhelmsöher Allee 73, 34121 Kassel, (October 2008)
P. Baer, R. Reichle, M. Zapf, T. Weise, and K. Geihs. Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems, page 43--52. IEEE, IEEE, (March 2007)
M. Khan, R. Reichle, and K. Geihs. Model-Driven Software Adaptation (M-ADAPT'07) at The European Conference on Object-Oriented Programming (ecoop07), 1, page 13-22. (July 2007)
T. Weise, K. Geihs, and P. Baer. Proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms ICANNGA'07, Part 1, volume 4431 of Lecture Notes in Computer Science (LNCS), page 167--173. Warsaw University of Technology, Warszawa, Poland, Springer Berlin Heidelberg New York, (April 2007)http://www.it-weise.de/documents/index.html#WGB2007DGPFb.