Skip to main content

Shared Context for Knowledge Distribution: A Case Study of Collaborative Taggings

  • Conference paper
New Frontiers in Applied Artificial Intelligence (IEA/AIE 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5027))

Abstract

Many existing knowledge management systems have been employing blogging services which is capable of providing various services to people. However, content delivering service among bloggers is not taking into account context (or semantics) of the contents, so that the service can spread irrelevant information into blogs. In order to solve this problem, this study proposes a blog context overlay network architecture for context matching between blogs. It is referred to as detecting “shared” context Thus, we can identify a community of practice (CoP) on blogosphere, with respect to contexts. As a result, newly generated knowledge can be proactively diffused to the blogs of which context is relevant to the knowledge, before the bloggers’ queries are asked.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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.

References

  1. Jung, J.J., Euzenat, J.: Towards semantic social networks. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, pp. 267–280. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  2. Jung, J.J., Koo, C.M.: Contextual matching-based blog overlay network for information sharing on blogoshphere. Telecommunication Review 17(4), 651–659 (2007)

    Google Scholar 

  3. Wasserman, S., Faust, K.: Social Network Analysis. Cambridge University Press, Cambridge (1994)

    Google Scholar 

  4. Chan, Y.S., Ng, H.T.: Word sense disambiguation with distribution estimation. In: Kaelbling, L.P., Saffiotti, A. (eds.) Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI 2005), Edinburgh, Scotland, UK, July 30-August 5, Professional Book Center, pp. 1010–1015 (2005)

    Google Scholar 

  5. Curtis, J., Cabral, J., Baxter, D.: On the application of the Cyc ontology to word sense disambiguation. In: Sutcliffe, G., Goebel, R. (eds.) Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, Melbourne Beach, Florida, USA, May 11-13, 2006, pp. 652–657. AAAI Press, Menlo Park (2006)

    Google Scholar 

  6. Borgatti, S.P., Everett, M.G.: Network analysis of 2-mode data. Social Networks 19(3), 243–269 (1997)

    Article  MathSciNet  Google Scholar 

  7. Roberts, J.M.: Correspondence analysis of two-mode network data. Social Networks 22(1), 65–72 (2000)

    Article  Google Scholar 

  8. Tantipathananandh, C., Berger-Wolf, T., Kempe, D.: A framework for community identification in dynamic social networks. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data mining (KDD 2007), pp. 717–726 (2007)

    Google Scholar 

  9. 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 

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

    Article  MATH  MathSciNet  Google Scholar 

  11. Jung, J.J.: Collaborative web browsing based on semantic extraction of user interests with bookmarks. Journal of Universal Computer Science 11(2), 213–228 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Ngoc Thanh Nguyen Leszek Borzemski Adam Grzech Moonis Ali

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Jung, J.J. (2008). Shared Context for Knowledge Distribution: A Case Study of Collaborative Taggings. In: Nguyen, N.T., Borzemski, L., Grzech, A., Ali, M. (eds) New Frontiers in Applied Artificial Intelligence. IEA/AIE 2008. Lecture Notes in Computer Science(), vol 5027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69052-8_67

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-69052-8_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69045-0

  • Online ISBN: 978-3-540-69052-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics