Scaling of knowledge in random conceptual networks

Lora J. Durak, Alfred W. Hübler

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

Abstract

We use a weighted count of the number of nodes and relations in a conceptual network as a measure for knowledge. We study how a limited knowledge of the prerequisite concepts affects the knowledge of a discipline. We find that the practical knowledge and expert knowledge scale with the knowledge of prerequisite concepts, and increase hyperexponentially with the knowledge of the discipline specific concepts. We investigate the maximum achievable level of abstraction as a function of the material covered in a text. We discuss possible applications for student assessment.

Original languageEnglish (US)
Title of host publicationComputational Science – ICCS 2001 - International Conference, Proceedings
EditorsVassil N. Alexandrov, Jack J. Dongarra, Benjoe A. Juliano, Rene S. Renner, C.J. Kenneth Tan
PublisherSpringer-Verlag Berlin Heidelberg
Pages976-985
Number of pages10
ISBN (Print)3540422331, 9783540422334
DOIs
StatePublished - 2001
EventInternational Conference on Computational Science, ICCS 2001 - San Francisco, United States
Duration: May 28 2001May 30 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2074
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Computational Science, ICCS 2001
CountryUnited States
CitySan Francisco
Period5/28/015/30/01

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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