Analyzing skill sets with or-relation tables in knowledge spaces

Feifei Xu, D. Miao, Yiyu Yao, Lai Wei
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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.
使用知识空间中的或关系表分析技能集
知识空间中技能图的析取模型可以基于技能与问题之间的或二元关系表来解释。可能存在一些技能是其他技能的结合。省略这些技能不会改变知识结构。寻找一个最小的技能集可以类似于粗糙集理论中的属性约简问题,其中使用了一个和二元关系表。本文考虑了一个知识空间析取模型的or-relation技能问题表。定义了最小技能集,并提出了寻找最小技能集的算法。用一个例子来说明基本思想。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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