Detecting Ontology Change from Application Data Flows | SpringerLink
Skip to main content

Detecting Ontology Change from Application Data Flows

  • Conference paper
On the Move to Meaningful Internet Systems 2005: OTM 2005 Workshops (OTM 2005)

Abstract

In this paper we describe a clustering process selecting a set of typical instances from a document flow. These representatives are viewed as semi-structured descriptions of domain categories expressed in a standard semantic web format, such as OWL [15]. The resulting bottom-up ontology may be used to check and/or update existing domain ontologies used by the e-business infrastructure.

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

Access this chapter

Subscribe and save

Springer+ Basic
¥17,985 /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
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 14523
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

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. Andersson, M.: Extracting an Entity Relationship Schema from a Relational Database through Reverse Engineering. In: Loucopoulos, P. (ed.) ER 1994. LNCS, vol. 881, Springer, Heidelberg (1994)

    Google Scholar 

  2. Ceravolo, P., Nocerino, M.C., Viviani, M.: Knowledge extraction from semi-structured data based on fuzzy techniques. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds.) KES 2004. LNCS (LNAI), vol. 3215, pp. 328–334. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  3. Chalupsk, H.: OntoMorph: A translation system for symbolic logic. In: Cohn, A.G., Giunchiglia, F., Selman, B. (eds.) KR 2000: Principles of Knowledge Representation and Reasoning, pp. 471–482. Morgan Kaufmann, San Francisco (2000)

    Google Scholar 

  4. Damiani, E., Nocerino, M.C., Viviani, M.: Knowledge Extraction from an XML Data Flow: Building a Taxonomy based on Clustering Technique. In: EUROFUSE Workshop on Data and Knowledge Engineering (EUROFUSE 2004), Warszawa, Poland, pp. 22–25 (2004)

    Google Scholar 

  5. Heflin, J., Hendler, J.: Dynamic ontologies on the web. In: Proceedings of the Seventeenth National Conference on Artificial Intelligence, pp. 443–449. AAAI/MIT Press (2000)

    Google Scholar 

  6. Horrocks, I., Sattler, U., Tobies, S.: Practical reason- ing for very expressive description logics. J. of the Interest Group in Pure and Applied Logic 8(3), 239–264 (2000)

    MATH  MathSciNet  Google Scholar 

  7. Koushik, S., Joodi, P.: E-Business Architecture Design Issues, IT Professional. In: IEEE Educational Activities Department, Piscataway, NJ, USA, vol. 2(3), pp. 38–43 (2000)

    Google Scholar 

  8. Maedche, A., Staab, S.: Ontology Learning for the Semantic Web, IEEE Intelligent Systems (2001)

    Google Scholar 

  9. Popa, L., Velegrakis, Y., Miller, R.J.: Translating Web Data. In: The Proceedings of VLDB 2002, pp. 598–609 (2002)

    Google Scholar 

  10. Rodriguez-Gianolli, P., Mylopoulos, J.: A Semantic Approach to XML-based Data Integration. In: Kunii, H.S., Jajodia, S., Sølvberg, A. (eds.) ER 2001. LNCS, vol. 2224, pp. 117–132. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  11. Reynaud, C., Sirot, J.P., Vodislav, D.: Semantic Integration of XML Heterogeneous Data Sources. In: IDEAS, pp. 199–208. IEEE Computer Society, Los Alamitos (2001)

    Google Scholar 

  12. Visser, P.R.S., Jones, D.M., Bench-Capon, T.J.M., Shave, M.J.R.: An analysis of ontological mismatches: Heterogeneity versus interoperability. In: AAAI 1997 Spring Symposium on Ontological Engineering, Stanford, USA (1997)

    Google Scholar 

  13. SOAP Version 1.2 W3C Recommendation (June 24 2003), http://www.w3.org/TR/soap/

  14. ebXML SPECS, http://www.ebxml.org/specs/

  15. OWL Web Ontology Language Overview, W3C Recommendation (February 10 2004), http://www.w3.org/TR/2004/REC-owl-features-20040210/

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ceravolo, P., Damiani, E. (2005). Detecting Ontology Change from Application Data Flows. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems 2005: OTM 2005 Workshops. OTM 2005. Lecture Notes in Computer Science, vol 3762. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11575863_120

Download citation

  • DOI: https://doi.org/10.1007/11575863_120

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29739-0

  • Online ISBN: 978-3-540-32132-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics