Learning the syntax and semantic rules of an ECG grammar

Gabriella Kókai, János Csirik, Tibor Gyimóthy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this paper a learning system is presented that is able to learn both the syntax (from an over-generalized grammar) and semantic rules (containing threshold values and relations) of an ECG grammar. These rules are used to direct the classification of QRS complexes and to distinquish between QRS and non-QRS patterns. The system demonstrates how a theory revision method can be used to refine large Prolog programs.

Original languageEnglish
Title of host publicationAI*IA 97
Subtitle of host publicationAdvances in Artificial Intelligence - 5th Congress of the Italian Association for Artificial Intelligence, Proceedings
EditorsMaurizio Lenzerini
PublisherSpringer Verlag
Pages171-182
Number of pages12
ISBN (Print)3540635769, 9783540635765
Publication statusPublished - Jan 1 1997
Event5th Congress of the Italian Association for Artificial Intelligence, AI*IA 1997 - Rome, Italy
Duration: Sep 17 1997Sep 19 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1321
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th Congress of the Italian Association for Artificial Intelligence, AI*IA 1997
CountryItaly
CityRome
Period9/17/979/19/97

Keywords

  • ECG
  • Inductive logic programming
  • Syntactic pattern recognition

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kókai, G., Csirik, J., & Gyimóthy, T. (1997). Learning the syntax and semantic rules of an ECG grammar. In M. Lenzerini (Ed.), AI*IA 97: Advances in Artificial Intelligence - 5th Congress of the Italian Association for Artificial Intelligence, Proceedings (pp. 171-182). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1321). Springer Verlag.