Advertisement

Question Answering and Information Extraction from Texts

  • J. Kontos
  • I. Malagardi
Part of the International Series on Microprocessor-Based and Intelligent Systems Engineering book series (ISCA, volume 21)

Abstract

The research presented in this chapter is part of a project which aims at the development of a novel method for information extraction and knowledge acquisition from texts combined with question answering. The present state of the art in information extraction [1, 2] is based on the template approach. The template approach relies on a predefined user model which guides the extraction of information and the instantiation of a template as the result of the extraction process.

Keywords

Noun Phrase Natural Language Processing Machine Translation Information Extraction Elastic Force 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1].
    Cowie, J., and W. Lehnert. Information Extraction. Communications of the ACM. Vol. 39, No. 1, pp. 80–91, 1996[11].CrossRefGoogle Scholar
  2. [2].
    Pazienza, M. T. Information Extraction. LNAI Tutorial. Springer, 1997.Google Scholar
  3. [3].
    Kontos, J. Syntax-Directed Processing of Texts with Action Semantics. Cybernetica, 23, 2 pp. 157–175, 1980.Google Scholar
  4. [4].
    Kontos, J. Syntax-Directed Plan Recognition with a Microcomputer. Microprocessing and Microprogramming. 9, pp. 227–279, 1982.CrossRefGoogle Scholar
  5. [5].
    Kontos, J. Syntax-Directed Fact Retrieval from Texts with a Micro-Computer. Proc. [12]MELECON ′83, Athens, 1983.Google Scholar
  6. [6].
    Kontos, J. Natural Language Processing of Scientific/Technical Data, Knowledge and Text Bases. Proceedings of ARTINT Workshop. Luxembourg, 1985.Google Scholar
  7. [7].
    Kontos, J. ARISTA: Knowledge Engineering with Scientific Texts. Information and Software Technology, Vol. 34, No 9, pp. 611–616, 1992.CrossRefGoogle Scholar
  8. [8].
    Kontos, J. Artificial Intelligence and Natural Language Processing (In Greek) E. Benou, Athens, Greece, 1996.Google Scholar
  9. [9].
    Malagardi, I. Comparative Analysis of “na” and “ya na” sentences of the Greek language with the equivalent structures of German language and related problems in their machine translation. Unpublished Dissertation. University of Athens, 1995a.Google Scholar
  10. [10].
    Malagardi, I. The resolution of the subject ambiguity in sentences with “ya na” using domain knowledge, and related problems in machine translation. Proceedings of 2nd. International Congress on Greek Linguistics. Salzburg, 1995b.Google Scholar
  11. [11].
    Malagardi, I. Computer Determination of Relations between the Elements in Noun Phrases of Sublanguages. 17th annual meeting of the Department of Linguistics. Aristotle Univ. of Thessaloniki, 1996.Google Scholar
  12. [12].
    Guyton, A. C. Textbook of Medical Physiology. Eighth Edition, An HBJ International Edition. W.B. Saunders, 1991.Google Scholar
  13. [13].
    Willets, R. F. The Law Code of Gortyn. Kadmos: Supplement I. Berlin, 1967.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1999

Authors and Affiliations

  • J. Kontos
    • 1
  • I. Malagardi
    • 1
  1. 1.Department of InformaticsAthens University of Economics & BusinessAthensGreece

Personalised recommendations