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.
J. Mueller, and G. Stumme. 9th International ACM Web Science Conference 2017 (WebSci 2017), Troy, NY, USA, June 26-28, 2017. Accepted for Publication, New York, NY, USA, ACM, (June 2017)
J. Mueller, and G. Stumme. 9th International ACM Web Science Conference 2017 (WebSci 2017), Troy, NY, USA, June 26-28, 2017. Accepted for Publication, New York, NY, USA, ACM, (June 2017)
S. Sigg, S. Haseloff, and K. David. Proceedings of the 5th Workshop on Applications of Wireless Communications, page 31-45. Lappeenranta, Finland, Acta Universitatis Lappeenrantaensis, (August 2007)
S. Sigg, S. Haseloff, and K. David. Proceedings of the 5th Workshop on Applications of Wireless Communications (WAWC'07), Lappeenranta, Finland, (August 2007)
P. Lücking, K. Rohlfing, B. Wrede, and M. Schilling. 2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), page 210-216. IEEE, (2016)
P. Lücking, K. Rohlfing, B. Wrede, and M. Schilling. 2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), page 210-216. IEEE, (2016)
D. Durward, I. Blohm, and J. Leimeister. The Digital Economy And The Single Market - Employment Prospects And Working Conditions in Europe, FEPS - Foundation for European Progressive Studies, (2016)
A. Faulhaber, M. Hoppe, and L. Schmidt. 28th IEEE Conference on Virtual Reality and 3D User Interfaces: Abstracts and Workshops (Christchurch 2022), page 586–587. Piscataway, IEEE, (2022)
C. Ochs. Connect & Divide: The Practice Turn in Media Studies, Zürich, 3rd Media Studies Symposion of the German Research Foundation 2015, Diaphanes, (erscheint 2017)
C. Ochs. Connect & Divide: The Practice Turn in Media Studies. 3rd Media Studies Symposion of the German Research Foundation 2015, Diaphanes, Zürich, (2017)