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                                       Details for article 4 of 5 found articles
 
 
  Knowledge Acquisition under Incomplete Knowledge using Methods from Formal Concept Analysis: Part I
 
 
Title: Knowledge Acquisition under Incomplete Knowledge using Methods from Formal Concept Analysis: Part I
Author: Richard Holzer

Appeared in: Fundamenta informaticae
Paging: Volume 63 (2004) nr. 1 pages 17-39
Year: 2004-11-30
Contents: Formal contexts with unknown entries can be represented by three-valued contexts K=(G, M, {×, o, ?}, I), where a question mark indicates that it is not known whether the object g∈G has the attribute m∈M. To describe logical formulas between columns of such incomplete contexts the Kripke-semantics are used for propositional formulas over the set M of attributes. Attribute implications are considered as special propositional formulas. If a context is too large to be fully represented, an interactive computer algorithm may help the user to get maximal information (with respect to his knowledge) about the valid attribute implications of the unknown context. This computer algorithm is called "attribute exploration".
Publisher: IOS Press
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

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