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Knowledge Spaces with Graded Knowledge States

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F09%3A00010065" target="_blank" >RIV/61989592:15310/09:00010065 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Knowledge Spaces with Graded Knowledge States

  • Original language description

    Knowledge spaces represent a framework for assessment of knowledge for which solid theoretical foundations, methodology, software tools and numerous practical applications are available. The underlying assumption in knowledge spaces is that a knowledge state of an individual is represented by a set of items/questions which the individual has mastered/is capable of answering. In this paper, we propose an extension of knowledge spaces which accounts for gradedness of knowledge states. Namely, more often than not, to assess whether an individual has mastered an item is a matter of degree. We assume that a knowledge state is represented by a graded set with grades representing degrees to which an individual has mastered the items. The scale of grades becomes a parameter of our approach. If 0 and 1 are the only grades, our approach coincides with that of ordinary knowledge spaces. We develop basic concepts and results in the graded setting including bases of graded knowledge states and thei

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BD - Information theory

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2009

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    International Symposium on Knowledge Acquisition and Modeling

  • ISBN

    978-0-7695-3488-6

  • ISSN

  • e-ISSN

  • Number of pages

    1500

  • Pages from-to

  • Publisher name

    IEEE Computer Society Press

  • Place of publication

    New York

  • Event location

  • Event date

  • Type of event by nationality

  • UT code for WoS article