Paper Info
Title
Analyzing Skill Sets With Or-Relation Tables In Knowledge Spaces
Abstract
The disjunctive model of skill map in knowledge spaces can be interpreted based on an or-binary relation table between skills and questions. There may exist skills that are the union of other skills. Omitting these skills will not change the knowledge structure. Finding a minimal skill set may be formulated similar to the problem of attribute reduction in rough set theory, where an and-binary relation table is used In this paper, an or-relation skill-question table is considered for a disjunctive,e model of knowledge spaces. A minimal skill set is defined and an algorithm for finding the minimal skill set is proposed. An example is used to illustrate the basic idea.
Year
DOI
Venue
2009
10.1109/COGINF.2009.5250759
PROCEEDINGS OF THE 8TH IEEE INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS
Keywords
Field
DocType
information processing,machine intelligence,rough set theory,set theory,data mining,psychology,approximation algorithms,cognitive science,artificial intelligence,cognition,binary relation,space technology
Set theory,Approximation algorithm,Cognitive systems,Cognitive informatics,Rough set,Knowledge structure,Artificial intelligence,Mathematics,Knowledge acquisition
Conference
Citations 
PageRank 
References 
0
0.34
21
Authors
4
Name
Order
Citations
PageRank
Feifei Xu1765.25
Duoqian Miao21854119.26
Y. Y. Yao39707674.28
Lai Wei4412.73