Skip to main content

Dynamic Profiling for Efficiency Searching System in Distributed Computing

  • Conference paper
Book cover Future Generation Information Technology (FGIT 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6485))

Included in the following conference series:

  • 1969 Accesses

Abstract

RFID technology that identifies objects on request of dynamic linking and tracking is composed of application components supporting information infrastructure. Despite their many advantages, existing applications, which do not consider elements related to real-time data communication among remote devices, cannot support connections among heterogeneous devices effectively. As different network devices are installed in applications separately and go through different query analysis processes, there happen the delays of monitoring or errors in data conversion. This paper proposes recommendation service that can update and reflect personalized profiles dynamically in Distributed Computing environment for integrated management of information extracted from RFID tags regardless of application. The advanced personalized module helps the service recommendation server make regular synchronization with the personalized profile. The proposed system can speed and easily extend the matching of services to user profiles and matching between user profiles or between services. Finally dynamic profiling help to reduce the development investment, improve the system’s reliability, make progress in the standardization of real-time data processing in matching searching system.

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. Zhou, X., Wu, S.-T., Li, Y., Xu, Y., Lau, R.Y.K., Bruza, P.D.: Utilizing Search Internet in Topic Ontology-based User Profile for Web Mining. In: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence (2006)

    Google Scholar 

  2. Kobayashi, I., Saito, M.: A Study on Information Recommendation System that Provides Topical Information Related to User’s Inquiry for Information Retrieval. In: Web Intelligence and International Agent Technology Workshops, pp. 385–388 (2006)

    Google Scholar 

  3. Jung, K.Y., Lee, J.H.: User Preference Mining through Hybrid Collaborative Filtering and Content-based Filtering in Recommendation System. IEICE Transaction on Information and Systems E87-D(12), 2781–2790 (2004)

    Google Scholar 

  4. Keenoy, K., Levene, M.: Personalization of web search. In: Mobasher, B., Anand, S.S. (eds.) ITWP 2003. LNCS (LNAI), vol. 3169, pp. 201–228. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  5. Miller, B.N., Konstan, J.A., Miller, J.R., Konstan, J.A., Pocketlens, J.R.: PocketLens: Toward a Personal Recommender System. ACM Transactions on Information Systems (TOIS) 22(3), 437–476 (2004)

    Article  Google Scholar 

  6. Kim, Y.H., Kim, B.G., Lim, H.C.: The index organizations for RDF and RDF schema. In: ICACT 2006, vol. 3, pp. 1871–1874 (2006)

    Google Scholar 

  7. Beckett, D.: RDF/XML Syntax Specification, W3C (2004)

    Google Scholar 

  8. Baader, F., Horrocks, I., Sattler, U.: Description Logics as Ontology Languages for the Semantic Web. In: Hutter, D., Stephan, W. (eds.) Mechanizing Mathematical Reasoning. LNCS (LNAI), vol. 2605, pp. 228–248. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  9. Huang, H., Liu, C.C., Zhou, X.J.: Bayesian approach to transforming public gene expression repositories into disease diagnosis databases. Proc. Natl. Acad. Sci., 6823–6828 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Song, CW., Kim, TG., Chung, KY., Rim, KW., Lee, JH. (2010). Dynamic Profiling for Efficiency Searching System in Distributed Computing. In: Kim, Th., Lee, Yh., Kang, BH., Ślęzak, D. (eds) Future Generation Information Technology. FGIT 2010. Lecture Notes in Computer Science, vol 6485. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17569-5_51

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-17569-5_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17568-8

  • Online ISBN: 978-3-642-17569-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics