摘要
[目的/意义]面对高校信息呈现碎片化的趋势,提出高校信息碎片化整合流程,并应用随机森林算法构建高校信息碎片化整合的特征选择模型。[方法/过程]基于高校信息整合的发展现状与存在问题,分析随机森林算法原理及优势,将其运用到高校信息碎片化整合过程的特征选择模型中,并以高校贫困生认定为例,对该模型加以验证。[结果/结论]随机森林算法在高校信息整合特征选择上表现出较高的准确性和有效性,为高校信息碎片化整合提供了一种新的思路。
[ Purpose/significance] Facing the trend of fragmentation of university information, this paper puts forward the integration process of fragmented university information, and applies the random forest algorithm to construct the feature selection model of information-fragmented integration in universities. [ Method/process] This paper represents the development, research status and existing problems of university information integration. Furthermore, in this paper, we elaborate the principles and advantages of the random forest algorithm, and use it to the feature selection model of information fragmented integration process in universities. Finally, we validate the model by using the example of identifying the students in the need of financial help. [Result/conclusion] Random forest algorithm shows higher accuracy and validity in the selection of features for integrating university information and therefore provides a new way for the integration of fragmented university information.
作者
张文德
程涵
刘田
曾金晶
Zhang Wende;Cheng Han;Liu Tian;Zeng Jinjing(Institute of Information Management, Fuzhou University, Fuzhou 350108;Library of Fujian Agriculture and Forestry University, Fuzhou 350002)
出处
《图书情报工作》
CSSCI
北大核心
2018年第7期119-124,共6页
Library and Information Service
基金
中国高教学会2016年度教育信息化专项课题“基于高校信息碎片化的信息整合构建研究”(项目编号:2016XXZD01)
2016年福建省教育厅中青年项目“基于不含有主键大数据精简的直觉模糊决策方法及其应用研究”(项目编号:JAT160097)
“基于中智集的高校信息系统安全风险评方法研究”(项目编号:JAT160094)研究成果之一
关键词
随机森林
碎片化
信息整合
特征选择
random forest fragmentation information integration feature selection