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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摘要在现存构建知识结构的模型中,以同一知识结构评价个体的知识掌握情况并不合理.为此,文中主要针对如下两个问题展开研究:技能映射通过析取模型、合取模型与能力模型诱导知识结构的条件过于宽松或苛刻,不同技能子集在同一模型下可能诱导相同知识状态.首先,介绍技能包含度和能力包含度的概念,建立构建知识结构的变精度α-模型和变精度α-能力模型.再讨论诱导良级知识结构时技能映射需满足的条件,得到良好技能映射诱导的知识结构均为良级知识结构的结果.然后,针对技能映射和技能函数存在等价技能子集的情况,分别考虑保持知识结构不变的技能子集约简及学习路径选择的问题,并给出获取极小技能子集族和知识结构的算法.最后,在6个数据集上的实验验证文中算法的可行性和有效性.

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	杨桃丽
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	林艺东

关键词 ：知识结构, 技能映射, 变精度模型, 良级知识结构, 技能子集约简, 学习路径

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

收稿日期: 2022-01-07

ZTFLH:

TP182

基金资助:国家自然科学基金项目(No.11871259)、福建省自然科学基金项目(No.2019J01748,2020J02043)、福建省中青年基金项目(No.JAT210255)资助

通讯作者: 李进金,博士,教授,主要研究方向为信息技术、不确定性的数学理论与方法.E-mail:jinjinlimnu@126.com.

作者简介: 杨桃丽,硕士研究生,主要研究方向为知识空间理论.E-mail:yangtaoli2019@163.com.
李招文,博士,教授,主要研究方向为拓扑及其应用、粗糙集、模糊集、信息系统.E-mail:lizhaowen8846@126.com.
金铭,硕士研究生,主要研究方向为粗糙集.E-mail:jinming149@163.com.
周银凤,硕士研究生,主要研究方向为知识空间理论.E-mail:j_jenifer@126. com.
林艺东,博士,副教授,主要研究方向为知识空间理论、形式概念分析、认知概念学习.E-mail:yidong_lin@yeah.net.

引用本文:

杨桃丽, 李进金, 李招文, 金铭, 周银凤, 林艺东. 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[J]. 模式识别与人工智能, 2022, 35(8): 671-687. YANG Taoli, LI Jinjin, LI Zhaowen, JIN Ming, ZHOU Yinfeng, Lin Yidong. Two Kinds of Variable Precision Models Based on Skill for Constructing Knowledge Structures and Skill Subset Reduction. Pattern Recognition and Artificial Intelligence, 2022, 35(8): 671-687.

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