Title :
Analyzing skill sets with or-relation tables in knowledge spaces
Author :
Xu, Feifei ; Miao, Duoqian ; Yao, Yiyu ; Wei, Lai
Author_Institution :
Dept. of Comput. Sci. & Technol., Tongji Univ., Shanghai, China
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 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.
Keywords :
cognitive systems; knowledge acquisition; rough set theory; and-binary relation table; attribute reduction; disjunctive model; knowledge spaces; minimal skill set; or-binary relation table; or-relation tables; rough set theory; skill sets; Artificial intelligence; Cognition; Cognitive informatics; Cognitive science; Information processing; Knowledge acquisition; Machine intelligence; Psychology; Set theory; Space technology;
Conference_Titel :
Cognitive Informatics, 2009. ICCI '09. 8th IEEE International Conference on
Conference_Location :
Kowloon, Hong Kong
Print_ISBN :
978-1-4244-4642-1
DOI :
10.1109/COGINF.2009.5250759