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基于决策树的网上学习资源建设策略研究
引用本文:毛布,谢汶.基于决策树的网上学习资源建设策略研究[J].四川理工学院学报(自然科学版),2011,24(3):317-320.
作者姓名:毛布  谢汶
作者单位:1. 四川自贡广播电视大学,四川自贡,643000
2. 四川大学计算机学院,成都,610000
摘    要:现代远程教育中资源建设人员常常根据各类资源的特征进行分析,以便促进学员网上学习浏览。从数据挖掘技术的角度探讨基于资源特征的分析不仅能促进学员点击率,又能帮助制定相应的资源建设策略。文章介绍了决策树算法原理,讨论了网上学习资源的各项具体特征,应用计算实例说明资源的特征促进点击率决策树分类模型,利用工具Analysis Manager中的决策树方法进行促进点击率规则的数据挖掘。研究表明该应用是切实可行的。

关 键 词:资源特征  促进点击率  数据挖掘  决策树算法

Research on Construction Strategies for Online Learning Resources Based on Decision Tree
MAO Bu,XIE Wen.Research on Construction Strategies for Online Learning Resources Based on Decision Tree[J].Journal of Sichuan University of Science & Engineering:Natural Science Editton,2011,24(3):317-320.
Authors:MAO Bu  XIE Wen
Institution:1.Sichuan Zigong Broadcasting and TV University,Zigong 643000,China;2.College of Computer Science,Sichuan University,Chengdu 610000,China)
Abstract:Resources construction personnel of modern distance education often base their analysis on the characteristics of different types of resources so as to promote a student-oriented online learning and browsing.A DM-based approach to the analysis of resource characteristics can not only increase learning hits but help formulate related strategies on resources construction.This essay introduces basic theories of decision tree calculation and analyzes various specific features of online learning resources.Examples of calculation are also employed in this essay to demonstrate that resource characteristics are conducive to the construction of decision tree hitting module.The ending part of the essay features DM that promotes hitting rates by way of decision tree in Analysis Manager.Results have justified the feasibility of this application.
Keywords:resource characteristics  hitting rate promotion  data mining  decision tree calculation
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