Nothing Special   »   [go: up one dir, main page]

Skip to main content

A Comparison of Content-Based Tag Recommendations in Folksonomy Systems

  • Conference paper
Knowledge Processing and Data Analysis (KPP 2007, KONT 2007)

Abstract

Recommendation algorithms and multi-class classifiers can support users of social bookmarking systems in assigning tags to their bookmarks. Content based recommenders are the usual approach for facing the cold start problem, i.e., when a bookmark is uploaded for the first time and no information from other users can be exploited. In this paper, we evaluate several recommendation algorithms in a cold-start scenario on a large real-world dataset.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Basile, P., Gendarmi, D., Lanubile, F., Semeraro, G.: Recommending smart tags in a social bookmarking system. In: Bridging the Gap between Semantic Web and Web 2.0 (SemNet 2007), pp. 22–29 (2007)

    Google Scholar 

  2. Benz, D., Tso, K., Schmidt-Thieme, L.: Automatic bookmark classification: A collaborative approach. In: Proceedings of the Second Workshop on Innovations in Web Infrastructure (IWI 2006), Edinburgh, Scotland (2006)

    Google Scholar 

  3. Burke, R.: Hybrid recommender systems, survey and experiments. User Modeling and User Adapted Interaction 12(4), 331–370 (2002)

    Article  MATH  Google Scholar 

  4. Byde, A., Wan, H., Cayzer, S.: Personalized tag recommendations via tagging and content-based similarity metrics. In: Proceedings of the International Conference on Weblogs and Social Media, Boulder, Colorado, USA (March 2007)

    Google Scholar 

  5. Cattuto, C., Loreto, V., Pietronero, L.: Collaborative tagging and semiotic dynamics (May 2006), http://arxiv.org/abs/cs/0605015

  6. Cavnar, W.B., Trenkle, J.M.: N-gram-based text categorization. In: Proceedings of SDAIR 1994, 3rd Annual Symposium on Document Analysis and Information Retrieval, Las Vegas, US, pp. 161–175 (1994)

    Google Scholar 

  7. Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines (2001), Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm

  8. Dubinko, M., Kumar, R., Magnani, J., Novak, J., Raghavan, P., Tomkins, A.: Visualizing tags over time. In: Proc. of the 15th International WWW Conference, Edinburgh, Scotland (2006)

    Google Scholar 

  9. Firan, C.S., Nejdl, W., Paiu, R.: The benefit of using tag-based profiles. In: 5th Latin American Web Congress, Santiago de Chile, 31 October - 2 November (2007)

    Google Scholar 

  10. Halpin, H., Robu, V., Shepard, H.: The dynamics and semantics of collaborative tagging. In: Proceedings of the 1st Semantic Authoring and Annotation Workshop (SAAW 2006), Atlanta, Georgia, USA (2006)

    Google Scholar 

  11. Hammond, T., Hannay, T., Lund, B., Scott, J.: Social Bookmarking Tools (I): A General Review. D-Lib Magazine 11(4) (April 2005)

    Google Scholar 

  12. Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: Information Retrieval in Folksonomies: Search and Ranking. In: Sure, Y., Domingue, J. (eds.) ESWC 2006. LNCS, vol. 4011, pp. 411–426. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  13. Illig, J.: Machine learnability analysis of textclassifications in a social bookmarking folksonomy. Bachelor thesis. University of Kassel, Kassel (2008)

    Google Scholar 

  14. Jäschke, R., Marinho, L., Hotho, A., Schmidt-Thieme, L., Stumme, G.: Tag recommendations in social bookmarking systems. AI Communications 21(4), 231–247 (2008)

    MathSciNet  MATH  Google Scholar 

  15. Kim, S., Rim, H., Yook, D., Lim, H.: Effective methods for improving naive bayes text classifiers (2002)

    Google Scholar 

  16. Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. Journal of the ACM 46(5), 604–632 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  17. Li, S., Momoi, K.: A composite approach to language/encoding detection. In: 19th International Unicode Conference, San Jose, California, USA (2001)

    Google Scholar 

  18. Lund, B., Hammond, T., Flack, M., Hannay, T.: Social Bookmarking Tools (II): A Case Study - Connotea. D-Lib Magazine 11(4) (April 2005)

    Google Scholar 

  19. Mathes, A.: Folksonomies – Cooperative Classification and Communication Through Shared Metadata (December 2004), http://www.adammathes.com/academic/computer-mediated-communication/folksonomies.html

  20. Mika, P.: Ontologies Are Us: A Unified Model of Social Networks and Semantics. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 522–536. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  21. Mishne, G.: Autotag: a collaborative approach to automated tag assignment for weblog posts. In: WWW 2006: Proceedings of the 15th International Conference on World Wide Web, pp. 953–954. ACM Press, New York (2006)

    Google Scholar 

  22. Morik, K., Brockhausen, P., Joachims, T.: Combining statistical learning with a knowledge-based approach - a case study in intensive care monitoring. In: Bratko, I., Dzeroski, S. (eds.) Proceedings of the 16th International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27-30, pp. 268–277. Morgan-Kaufman Publishers, San Francisco (1999)

    Google Scholar 

  23. Schmitz, C., Hotho, A., Jäschke, R., Stumme, G.: Mining association rules in folksonomies. In: Batagelj, V., Bock, H.-H., Ferligoj, A., Žiberna, A. (eds.) Data Science and Classification: Proc. of the 10th IFCS Conf., Studies in Classification, Data Analysis, and Knowledge Organization, pp. 261–270. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  24. Sebastiani, F.: Machine learning in automated text categorization. ACM Computing Surveys 34(1), 1–47 (2002)

    Article  Google Scholar 

  25. Song, Y., Zhang, L., Lee Giles, C.: A sparse gaussian processes classification framework for fast tag suggestions. In: CIKM 2008: Proceeding of the 17th ACM Conference on Information and Knowledge Mining, pp. 93–102. ACM, New York (2008)

    Chapter  Google Scholar 

  26. Song, Y., Zhuang, Z., Li, H., Zhao, Q., Li, J., Lee, W.-C., Lee Giles, C.: Real-time automatic tag recommendation. In: SIGIR 2008: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 515–522. ACM, New York (2008)

    Google Scholar 

  27. Tso-Sutter, K., Marinho, L.B., Schmidt-Thieme, L.: Tag-aware recommender systems by fusion of collaborative filtering algorithms. In: Proceedings of 23rd Annual ACM Symposium on Applied Computing (SAC 2008), Edinburgh, Scotland (2007)

    Google Scholar 

  28. Xu, Y., Zhang, L., Liu, W.: Cubic analysis of social bookmarking for personalized recommendation. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds.) APWeb 2006. LNCS, vol. 3841, pp. 733–738. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  29. Xu, Z., Fu, Y., Mao, J., Su, D.: Towards the semantic web: Collaborative tag suggestions. In: Proceedings of the Collaborative Web Tagging Workshop at the WWW 2006, Edinburgh, Scotland (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Illig, J., Hotho, A., Jäschke, R., Stumme, G. (2011). A Comparison of Content-Based Tag Recommendations in Folksonomy Systems. In: Wolff, K.E., Palchunov, D.E., Zagoruiko, N.G., Andelfinger, U. (eds) Knowledge Processing and Data Analysis. KPP KONT 2007 2007. Lecture Notes in Computer Science(), vol 6581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22140-8_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-22140-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22139-2

  • Online ISBN: 978-3-642-22140-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics