基于知识图谱的自适应学习系统知识模型构建  

Knowledge Model of Adaptive Learning System Based on Knowledge Map

作　　者：朱艳茹 范亚芹[1] 赵洋[1] ZHU Yanm;FAN Yaqin;ZHAO Yang(College of Communacation Engineering, Jilin University, Changchun 130012, China)

机构地区：[1]吉林大学通信工程学院,长春130012

出　　处：《吉林大学学报（信息科学版）》2018年第3期345-350,共6页Journal of Jilin University（Information Science Edition）

摘　　要：为解决在线学习平台中知识表现离散、系统性不高和知识模型适用性差等问题,提出基于知识图谱的知识模型构建,再利用FP-Growth数据挖掘算法进行关联规则挖掘,实现知识模型的动态更新。通过实践证明,知识图谱可有效改善知识模型的系统性,FP-Growth算法充分考虑了学生因素对知识模型的影响,提高了模型的适用性。In order to solve the problem of discrete knowledge,poor systematization and poor applicability of knowledge model in online learning platform. We propose a knowledge model based on knowledge map,and then use the FP-Growth data mining algorithm to mining association rules to update knowledge model. Practice shows that the knowledge map can effectively improve the systematicness of the knowledge model. The FP-Growth algorithm fully considers the influence of student factors on the knowledge model and improves the applicability of the model.

关 键 词：知识模型 知识图谱 数据挖掘 FP-GROWTH算法 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]