Evaluation of the FastFIX Prototype 5Cs CARD System

Megan Vazey, Debbie Richards

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

2 Citations (Scopus)

Abstract

The 5Cs architecture offers a hybrid Case And Rule-Driven (CARD) system that supports the Collaborative generation and refinement of a relational structure of Cases, ConditionNodes, Classifications, and Conclusions (hence 5Cs). It stretches the Multiple Classification Ripple Down Rules (MCRDR) algorithm and data structure to encompass collaborative classification, classification merging, and classification re-use. As well, it offers a very lightweight collaborative indexing tool that can act as an information broker to knowledge resources across an organisation’s Intranet or across the broader Internet, and it supports the coexistence of multiple truths in the knowledge base. This paper reports the results of the software trial of the FastFIX prototype - an early implementation of the 5Cs model, in a 24×7 high-volume ICT support centre.

Original languageEnglish
Title of host publicationAdvances in knowledge acquisition and management
Place of PublicationBerlin, Germany
PublisherSpringer, Springer Nature
Pages108-119
Number of pages12
ISBN (Print)9783540689553
DOIs
Publication statusPublished - 2006
EventPacific Rim Knowledge AcquisitionWorkshop, PKAW 2006 - Guilin, China
Duration: 7 Aug 20068 Aug 2006

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume4303
ISSN (Print)1611-3349

Other

OtherPacific Rim Knowledge AcquisitionWorkshop, PKAW 2006
CountryChina
CityGuilin
Period7/08/068/08/06

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Keywords

  • single classification ripple down rules
  • multiple classification ripple down rules
  • knowledge acquisition
  • top-down rule-driven
  • bottom-up case-driven
  • artificial intelligence

Cite this

Vazey, M., & Richards, D. (2006). Evaluation of the FastFIX Prototype 5Cs CARD System. In Advances in knowledge acquisition and management (pp. 108-119). (Lecture Notes in Computer Science; Vol. 4303). Berlin, Germany: Springer, Springer Nature. https://doi.org/10.1007/11961239_10