Complex information management using a framework supported by ECA rules in XML

Bing Wu, Essam Mansour, Kudakwashe Dube

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

4 Citations (Scopus)

Abstract

It is every organization's desire to incorporate best practice into its enterprise. This incorporation gives rise to the need to maintain information that could be viewed as complex. Managing this complex information poses a major challenge to the area of information management. This paper presents a framework for the incorporation of best practice and subsequent management of the resulting complex information. The paper also presents an approach to supporting this framework by using the ECA rule paradigm with an XML-based language, called AIM, for specifying and querying best practice and the complex information.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages224-231
Number of pages8
Volume4824 LNCS
Publication statusPublished - 1 Dec 2007
Externally publishedYes
EventInternational Symposium on Rule Interchange and Applications, RuleML-2007 - Orlando, FL, United States
Duration: 25 Oct 200726 Oct 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4824 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherInternational Symposium on Rule Interchange and Applications, RuleML-2007
CountryUnited States
CityOrlando, FL
Period25/10/0726/10/07

Fingerprint

Information Management
Practice Guidelines
XML
Information management
Best Practice
Industry
Practice Management
Language
Paradigm
Framework

Keywords

  • Active database
  • ECA rule paradigm
  • Information management
  • Rule markup languages
  • XML

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Wu, B., Mansour, E., & Dube, K. (2007). Complex information management using a framework supported by ECA rules in XML. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4824 LNCS, pp. 224-231). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4824 LNCS).

Complex information management using a framework supported by ECA rules in XML. / Wu, Bing; Mansour, Essam; Dube, Kudakwashe.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4824 LNCS 2007. p. 224-231 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4824 LNCS).

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

Wu, B, Mansour, E & Dube, K 2007, Complex information management using a framework supported by ECA rules in XML. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4824 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4824 LNCS, pp. 224-231, International Symposium on Rule Interchange and Applications, RuleML-2007, Orlando, FL, United States, 25/10/07.
Wu B, Mansour E, Dube K. Complex information management using a framework supported by ECA rules in XML. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4824 LNCS. 2007. p. 224-231. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Wu, Bing ; Mansour, Essam ; Dube, Kudakwashe. / Complex information management using a framework supported by ECA rules in XML. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4824 LNCS 2007. pp. 224-231 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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