Data mining clustering techniques in academia

被引：0
|
作者：
Bresfelean, Vasile Paul [1 ]
Bresfelean, Mihaela [1 ]
Ghisoiu, Nicolae [1 ]
Comes, Calin-Adrian
机构：
[1] Univ Babes Bolyai, Fac Econ & Business Adm, Cluj Napoca 400591, Romania
来源：
ICEIS 2007: PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS: ARTIFICIAL INTELLIGENCE AND DECISION SUPPORT SYSTEMS | 2007年
关键词：
cluster; data clustering; K-means algorithm; students; analysis; percentage relation;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In the present paper the authors exemplify the connections among the undergraduate studies, continuing education and professional enhancement on the foundations required by Romania's integration in EU's structures. The study was directed to the senior undergraduate students and master degree students from the Faculty of Economics and Business Administration, Babes-Bolyai University of Cluj-Napoca, using questionnaires in a collaborative approach, and processing the collected data by data mining clustering techniques, graphical and percentage representations, through Weka's implemented algorithms.
引用
收藏
页码：407 / 410
页数：4
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