Knowledge-Based Information Extraction: A Case Study of Recognizing Emails of Nigerian Frauds

  • Yanbin Gao
  • Gang Zhao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3513)


This paper describes the methodology, process and results of developing an application ontology as software specification of the semantics of forensics in the email suspicious of Nigerian frauds. Real life examples of fraud emails are analyzed for evidence and red flags to capture the underlying domain semantics with an application ontology of frauds. A model of the natural language structure in regular expressions is developed in the light of the ontology and applied to emails to extract linguistic evidences of frauds. The evaluation of the initial results shows a satisfactory recognition as an automatic fraud alert system. It also demonstrates a methodological significance: the methodical conceptual modeling and specific purpose-driven linguistic modeling are effective in encapsulating and managing their respective needs, perspectives and variability in real life linguistic processing applications.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Data Extraction Research Group at BYU,
  2. 2.
    Deray, T., Verheyden, P.: Towards a Semantic Integration of Medical Relational Databases by Using Ontologies: a Case Study. In: Meersman, R., Tari, Z. (eds.) OTM-WS 2003. LNCS, vol. 2889, pp. 137–150. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  3. 3.
    Jarrar, M., Demey, J., Meersman, R.: On Reusing Conceptual Data Modeling for Ontology Engineering. Journal on Data Semantics 1(1), 185–207 (2003)CrossRefGoogle Scholar
  4. 4.
    Kruchten, P.: The Rational Unified Process: An Introduction. Addison-Wesley, Reading (2000)Google Scholar
  5. 5.
    Meersman, R.: Reusing Certain Database Design Principles, Methods and Techniques for Ontology Theory, Construction and Methodology. STARLab Technical Report 01 (2000)Google Scholar
  6. 6.
  7. 7.
    Wigmore, J.H.: The Science of Judicial Proof as given by Logic, Psychology and General Experience. Boston, Little Brown (1937)Google Scholar
  8. 8.
    Gang, Z.: DOGMA-AKEM in FFpoirot. Draft report in WP6 of FFpoirot (2003) Google Scholar
  9. 9.
    Zhao, G., Gao, Y., Meersman, R.: An Ontology-based Approach to Business Modeling. In: Proceedings of the International Conference of Knowledge Engineering and Decision Support, pp. 213–221 (2004)Google Scholar
  10. 10.
    Zhao, G., Kingston, J., Kerremans, K., Coppens, F., Verlinden, R., Temmerman, R., Meersman, R.: Engineering an Ontology of Financial Securities Fraud. In: Meersman, R., Tari, Z., Corsaro, A. (eds.) OTM-WS 2004. LNCS, vol. 3292, pp. 605–620. Springer, Heidelberg (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yanbin Gao
    • 1
  • Gang Zhao
    • 2
  1. 1.Advanced System Development Co, LtdBeijingChina
  2. 2.STARLab, Computer Science DepartmentVrije Universiteit BrusselBelgium

Personalised recommendations