基于技能构建知识结构的两种变精度模型与技能子集约简

doi:10.16451/j.cnki.issn1003-6059.2022080001

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Abstract It is unreasonable to evaluate the knowledge mastery of different individuals by a same knowledge structure in the existing models of constructing knowledge structures. In this paper, two problems are mainly discussed. The conditions of knowledge structure delineated via disjunctive model, conjunctive model and competency model by a skill map are too loose or harsh, and the same knowledge state may be delineated by different skill subsets on the same model. Firstly, the concepts of skill inclusion degree and competency inclusion degree are introduced, and the variable precision α-model and variable precision α-competency model for constructing knowledge structures are established. Secondly, the conditions that a skill map should satisfy while delineating well-graded knowledge structures are discussed, and the result that the knowledge structures delineated by well-skill maps are well-graded knowledge structures is obtained. Then, in view of equivalent skill subsets existing in skill maps and skill functions, skill subset reduction keeping knowledge structure unchanged and learning path selection are studied, respectively. Algorithms for acquiring the family of minimal skill subsets and knowledge structures are given. Finally, experiments on 6 datasets show the feasibility and effectiveness of the proposed algorithms.

Key words： Knowledge Structure Skill Map Variable Precision Model Well-Graded Knowledge Structure Skill Subset Reduction Learning Path

Received: 07 January 2022

ZTFLH:

TP182

Fund:National Natural Science Foundation of China(No.11871259), Natural Science Foundation of Fujian Province(No.2019J01748,2020J02043), Young and Middle-Aged Foundation of Fujian Province(No.JAT210255)

Corresponding Authors: LI Jinjin, Ph.D., professor. His research interests include information technology, mathematical theories and methods of uncertainty.

About author:: YANG Taoli, master student. Her research interests include knowledge space theory.
LI Zhaowen, Ph.D., professor. His research interests include topology and its applications, rough set, fuzzy set and information systems.
JIN Ming, master student. Her research interests include rough set.
ZHOU Yinfeng, master student. Her research interests include knowledge space theory.
LIN Yidong, Ph.D., associate professor. His research interests include knowledge space theory, formal concept analysis and cognitive concept learning.

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Cite this article:

YANG Taoli,LI Jinjin,LI Zhaowen等. Two Kinds of Variable Precision Models Based on Skill for Constructing Knowledge Structures and Skill Subset Reduction[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(8): 671-687.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.2022080001 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2022/V35/I8/671

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