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K-Means聚类算法在毕业生就业信息分析中的实现 被引量:1

Realization of K-Means Clustering Algorithm in the Information Analysis of Graduate Employment
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摘要 摘要:聚类是指按照事物间的相似性对事物进行区分和分类的过程,是在无指导下自动进行的无监督分类。本文应用数据挖掘技术中的聚类分析,对毕业生就业信息进行研究,介绍了K-Means算法和K-Means算法在毕业生就业信息分析中的应用。 Clustering is a distinction between things and classification process which refers to things in accordance with the similarity.It is a non-supervised classification under the guidance of the non-automatic.Based on the cluster analysis of data mining technology,this article studies on the information of graduate employment,and introduces K-means algorithm and its application in the information analysis of graduate employment.
出处 《楚雄师范学院学报》 2009年第9期9-11,15,共4页 Journal of Chuxiong Normal University
关键词 数据挖掘 聚类分析 K-MEANS 就业分析 data mining cluster analysis K-Means employment analysis
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