Locally Expandable Allocation of Folksonomy Tags in a Directed Acyclic Graph

  • Takeharu Eda
  • Masatoshi Yoshikawa
  • Masashi Yamamuro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5175)


We propose a new classification system based on an analysis of folksonomy data. To find valuable resources from current social bookmark services, users need to specify search terms or tags, or to discover people with similar interests. Our system uses semantic relationships extracted from the co-occurrences of folksonomy data using PLSI and allocates folksonomy tags in a directed acyclic graph. Compared to the hierarchical allocation method of a tree, our method guarantees the number of children nodes and increases the number of available paths to an objective node, enabling users to navigate the resources using tags.


Child Node Cosine Similarity Semantic Space Probabilistic Latent Semantic Analysis Social Bookmark 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Brooks, C.H., Montanez, N.: Improved annotation of the blogosphere via autotagging and hierarchical clustering. In: Proc. International World Wide Web Conference, pp. 625–632. ACM Press, New York (2006)CrossRefGoogle Scholar
  2. 2.
    Yeung, C.A., Gibbins, N., Shadbolt, N.: Tag Meaning Disambiguation through Analysis of Tripartite Structure of Folksonomies. In: Proc. International Conferences on Web Intelligence and Intelligent Agent Technology (2007)Google Scholar
  3. 3.
    Dubinko, M., Kumar, R., Magnani, J., Novak, J., Raghavan, P., Tomkins, A.: Visualizing tags over time. In: Proc. International World Wide Web Conference. ACM Press, New York (2006)Google Scholar
  4. 4.
    Golder, S., Huberman, B.A.: The structure of collaborative tagging systems. Journal of Information Science (2006)Google Scholar
  5. 5.
    Heymann, P., Garcia-Molina, H.: Collaborative Creation of Communal Hierarchical Taxonomies in Social Tagging Systems. Technical report, http://heymann.stanford.edu/taghierarchy.html
  6. 6.
    Heymann, P., Koutrika, G., Garcia-Molina, H.: Can Social Bookmarking Improve Web Search? In: Proc. International Conference on Web Search and Data Mining (2008)Google Scholar
  7. 7.
    Hofmann, T.: Probabilistic latent semantic analysis. In: Proc of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm (1999)Google Scholar
  8. 8.
    Lee, L.: On the effectiveness of the skew divergence for statistical language analysis. In: Proc. International Workshop on Artificial Intelligence and Statistics, pp. 65–77 (2001)Google Scholar
  9. 9.
    Lux, M., Granitzer, M., Kern, R.: Aspects of Broad Folksonomies. In: Proc. International Conference on Database and Expert Systems Applications (2007)Google Scholar
  10. 10.
    Niwa, S., Doi, T., Honiden, S.: Web Page Recommender System based on Folksonomy Mining. In: Proc. International Conference on Information Technology: New Generations (2006)Google Scholar
  11. 11.
    Sabou, M., Gracia, J., Angeletou, S., dAquin1, M., Motta, E.: Evaluating the Semantic Web: A Task-Based Approach. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 423–437. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  12. 12.
    Sen, S., Lam, S.K., Rashid, A.M., Cosley, D., Frankowski, D., Osterhouse, J., Harper, M.F., Riedl, J.: Tagging, communities, vocabulary, evolution. In: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work. CSCW, New York, NY, USA, pp. 181–190 (2006)Google Scholar
  13. 13.
    Vo, J.: Tagging, Folksonomy & Co - Renaissance of Manual Indexing? unpublished (2007), http://arxiv.org/abs/cs/0701072v2
  14. 14.
    Wu, X., Zhang, L., Yu, Y.: Exploring Social Annotations for the Semantic Web. In: Proc. International World Wide Web Conference, pp. 417–426 (2006)Google Scholar
  15. 15.
    Yanbe, Y., Jatowt, A., Nakamura, S., Tanaka, K.: Can Social Bookmarking Enhance Search in the Web? In: Proceedings of the 7th ACM/IEEE Joint Conference on Digital Libraries (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Takeharu Eda
    • 1
    • 2
  • Masatoshi Yoshikawa
    • 2
  • Masashi Yamamuro
    • 1
  1. 1.NTT Cyber Space LaboratoriesJapan
  2. 2.Kyoto UniversityJapan

Personalised recommendations