KNN-Based Clustering for Improving Social Recommender Systems

  • Rong Pan
  • Peter Dolog
  • Guandong Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7607)


Clustering is useful in tag based recommenders to reduce sparsity of data and by doing so to improve also accuracy of recommendation. Strategy for the selection of tags for clusters has an impact on the accuracy. In this paper we propose a KNN based approach for ranking tag neighbors for tag selection. We study the approach in comparison to several baselines by using two datasets in different domains. We show, that in both cases the approach outperforms the compared approaches.


Tag Neighbors Clustering Personalization Recommender Systems Social Tagging 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bayyapu, K.R., Dolog, P.: Tag and Neighbour Based Recommender System for Medical Events. In: Proceedings of MEDEX 2010: The First International Workshop on Web Science and Information Exchange in the Medical Web Colocated with WWW 2010 Conference (2010)Google Scholar
  2. 2.
    Boratto, L., Carta, S., Ratc, V.E.: A robust automated tag clustering technique. In: Proceedings of the 10th International Proceedings on E-Commerce and Web Technologies, pp. 324–335 (2009)Google Scholar
  3. 3.
    Budura, A., Michel, S., Cudré-Mauroux, P., Aberer, K.: Neighborhood-Based Tag Prediction. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M., Simperl, E. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 608–622. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  4. 4.
    Burke, R.: Hybrid recommender systems: Survey and experiments. In: User Modeling and User Adapted Interaction, pp. 331–370. Springer, Heidelberg (2002)Google Scholar
  5. 5.
    Cao, L., Gorodetsky, V., Mitkas, P.: Agent mining: The synergy of agents and data mining. IEEE Intelligent Systems 24(3), 64–72 (2009)CrossRefGoogle Scholar
  6. 6.
    Cao, L., Luo, D., Zhang, C.: Ubiquitous Intelligence in Agent Mining. In: Cao, L., Gorodetsky, V., Liu, J., Weiss, G., Yu, P.S. (eds.) ADMI 2009. LNCS, vol. 5680, pp. 23–35. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    Chen, H., Dumais, S.: Bringing order to the web: automatically categorizing search results. In: CHI 2000: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 145–152. ACM, New York (2000)Google Scholar
  8. 8.
    van Dam, J.-W., Vandic, D., Hogenboom, F., Frasincar, F.: Searching and browsing tag spaces using the semantic tag clustering search framework. In: Proceedings of the 2010 IEEE Fourth International Conference on Semantic Computing, ICSC 2010, pp. 436–439. IEEE Computer Society, Washington, DC (2010)Google Scholar
  9. 9.
    Dasarathy, B.V.: Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques (1991)Google Scholar
  10. 10.
    Di Matteo, N.R., Peroni, S., Tamburini, F., Vitali, F.: A parametric architecture for tags clustering in folksonomic search engines. In: Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications, ISDA 2009, pp. 279–282. IEEE Computer Society, Washington, DC (2009)CrossRefGoogle Scholar
  11. 11.
    Gemmell, J., Schimoler, T., Mobasher, B., Burke, R.: Tag-Based Resource Recommendation in Social Annotation Applications. In: Konstan, J.A., Conejo, R., Marzo, J.L., Oliver, N. (eds.) UMAP 2011. LNCS, vol. 6787, pp. 111–122. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  12. 12.
    Guan, Z., Wang, C., Bu, J., Chen, C., Yang, K., Cai, D., He, X.: Document recommendation in social tagging services. In: Proceedings of the 19th International Conference on World Wide Web, WWW 2010, pp. 391–400. ACM, New York (2010)Google Scholar
  13. 13.
    Hayes, C., Avesani, P.: Using tags and clustering to identify topic-relevant blogs. In: International Conference on Weblogs and Social Media (March 2007)Google Scholar
  14. 14.
    Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: Folkrank: A ranking algorithm for folksonomies. In: LWA, pp. 111–114 (2006)Google Scholar
  15. 15.
    Zhou, J., Nie, X., Qin, L., Zhu, J.: Journal of ComputersGoogle Scholar
  16. 16.
    Gemmell, J., Schimoler, T., Mobasher, B., Burke, R.: Resource Recommendation in Collaborative Tagging Applications. In: Buccafurri, F., Semeraro, G. (eds.) EC-Web 2010. LNBIP, vol. 61, pp. 1–12. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  17. 17.
    Moemeng, C., Wang, C., Cao, L.: Obtaining an Optimal MAS Configuration for Agent-Enhanced Mining Using Constraint Optimization. In: Cao, L., Bazzan, A.L.C., Symeonidis, A.L., Gorodetsky, V.I., Weiss, G., Yu, P.S. (eds.) ADMI 2011. LNCS, vol. 7103, pp. 46–57. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  18. 18.
    Moemeng, C., Zhu, X., Cao, L.: Integrating Workflow into Agent-Based Distributed Data Mining Systems. In: Cao, L., Bazzan, A.L.C., Gorodetsky, V., Mitkas, P.A., Weiss, G., Yu, P.S. (eds.) ADMI 2010. LNCS, vol. 5980, pp. 4–15. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  19. 19.
    Pan, R., Xu, G., Dolog, P.: User and Document Group Approach of Clustering in Tagging Systems. In: Proceeding of the 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond, LWA 2010 (2010)Google Scholar
  20. 20.
    Pan, R., Xu, G., Dolog, P.: Improving recommendations in tag-based systems with spectral clustering of tag neighbors. In: Proceedings of The 3rd FTRA International Conference on Computer Science and its Applications (CSA 2011): Computer Science and Convergence. LNEE, vol. 114, Part I, pp. 355–364. Springer, Heidelberg (2011)Google Scholar
  21. 21.
    Shakhnarovish, D., Indyk: Nearest-Neighbor Methods in Learning and Vision. The MIT Press (2005)Google Scholar
  22. 22.
    Shepitsen, A., Gemmell, J., Mobasher, B., Burke, R.: Personalized recommendation in social tagging systems using hierarchical clustering. In: Proceedings of the 2008 ACM Conference on Recommender Systems, RecSys 2008, pp. 259–266. ACM, New York (2008)Google Scholar
  23. 23.
    Xu, G., Zong, Y., Pan, R., Dolog, P., Jin, P.: On Kernel Information Propagation for Tag Clustering in Social Annotation Systems. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds.) KES 2011, Part II. LNCS, vol. 6882, pp. 505–514. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  24. 24.
    Zong, Y., Xu, G., Jin, P., Zhang, Y., Chen, E., Pan, R.: APPECT: An Approximate Backbone-Based Clustering Algorithm for Tags. In: Tang, J., King, I., Chen, L., Wang, J. (eds.) ADMA 2011, Part I. LNCS, vol. 7120, pp. 175–189. Springer, Heidelberg (2011)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rong Pan
    • 1
  • Peter Dolog
    • 1
  • Guandong Xu
    • 2
  1. 1.Department of Computer ScienceAalborg UniversityDenmark
  2. 2.Centre for Applied InformaticsVictoria UniversityAustralia

Personalised recommendations