Potential Data Mining Classification Techniques for Academic Talent Forecasting

被引:1
作者
Jantan, Hamidah [1 ]
Hamdan, Abdul Razak [2 ]
Othman, Zulaiha Ali [2 ]
机构
[1] Univ Teknol MARA UiTM Terengganu, Fac Comp & Math Sci, Dungun 23000, Terengganu, Malaysia
[2] Univ Kebangsaan Malaysia, Fac Informat Sci & Technol, Bangi 43600, Malaysia
来源
2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS | 2009年
关键词
Data Mining; Classification Techniques; Academic Talent; and Forecasting; DECISION-TREE;
D O I
10.1109/ISDA.2009.64
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Classification and prediction are among the major techniques in Data mining and widely used in various fields. In this article we present a study on how some talent management problems can be solved using classification and prediction techniques in Data mining. By using this approach, the talent performance can be predicted by using past experience knowledge discovered from the existing database. In the experimental phase, we have used selected classification and prediction techniques to propose the appropriate techniques from our training dataset. An example is used to demonstrate the feasibility of the suggested classification techniques using academician performance data. Thus, by using the experiments results, we suggest the potential classification techniques for academic talent forecasting.
引用
收藏
页码:1173 / +
页数:2
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