Knowledge-based information extraction: a case study of recognizing emails of Nigerian frauds

  • Authors:
  • Yanbin Gao;Gang Zhao

  • Affiliations:
  • Advanced System Development Co, Ltd, Beijing, China;STARLab, Computer Science Department, Vrije Universiteit Brussel, Belgium

  • Venue:
  • NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

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.