计算机与现代化 ›› 2012, Vol. 1 ›› Issue (11): 22-25.doi: 10.3969/j.issn.1006-2475.2012.11.006

• 人工智能 • 上一篇    下一篇

序列模式挖掘在教学管理上的应用

王智钢1,2,王池社1,2,顾云锋1,田海梅1   

  1. 1.金陵科技学院信息技术学院,江苏 南京 211169;2.江苏省信息分析工程实验室,江苏 南京 211169
  • 收稿日期:2012-07-26 修回日期:1900-01-01 出版日期:2012-11-10 发布日期:2012-11-10

Sequential Pattern Mining Used in Teaching Management

WANG Zhi-gang1,2, WANG Chi-she1,2, GU Yun-feng1, TIAN Hai-mei1   

  1. 1. School of Information Technology, Jinling Institute of Technology, Nanjing 211169, China;2. Information Analysis Engineering Laboratory of Jiangsu Province, Nanjing 211169, China
  • Received:2012-07-26 Revised:1900-01-01 Online:2012-11-10 Published:2012-11-10

摘要: 序列模式挖掘是指从序列数据库中寻找频繁子序列作为模式的知识发现过程。本文将序列模式挖掘应用于教学管理,对学生成绩样本数据按照序列数据库模式进行建模和数据挖掘,得出置信度大于65%的时序关联规则3条。实验结果表明,将序列模式挖掘应用于教学管理,对相关课程成绩进行数据挖掘是可行的,发现的时序关联规则对学校的教学管理和学生学业促进有一定的实际指导意义。

关键词: 数据挖掘, 序列模式, 时序关联规则, 教学管理, 学业促进

Abstract: Sequential pattern mining is a knowledge discovery procession to look for frequent sub pattern from temporal sequence database. This paper applies sequential pattern mining to teaching management, constructs data model according to the temporal sequence database model on student achievement sample data, does sequential pattern mining, and gets three temporal sequence association rules whose confidence is higher than 65%. The experimental result indicates that applying sequence pattern mining to teaching management, and doing data mining on scores of relevant course is feasible. The found temporal sequential association rules have certain practical significance to improve the teaching management and promote the student's learning.

Key words: data mining, sequential pattern, temporal sequence association rules, teaching management, study promotion

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