| 量化关联规则在高校就业信息数据中的应用 |
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| 引用本文： | 张晓萍,朱玉全,陈耿. 量化关联规则在高校就业信息数据中的应用[J]. 计算机技术与发展, 2013, 0(11): 199-202,212 |
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| 作者姓名： | 张晓萍 朱玉全 陈耿 |
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| 作者单位： | [1]江苏大学计算机科学与通信工程学院,江苏镇江212013 [2]南京审计学院信息科学学院,江苏南京210029 |
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| 基金项目： | 国家自然科学基金资助项目（71271117）;江苏省科技型企业技术创新资金项目（BC2012201） |
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| 摘 要： | 针对就业信息数据中存在着大量的量化属性和分类属性等现象，提出了一种基于k-means的量化关联规则挖掘方法。该方法利用聚类算法k-means对量化属性进行合理分区，将量化属性转化为布尔型；利用改进的布尔关联规则方法对此进行关联规则挖掘，找出学生的受教育属性和就业属性之间的关联性；对挖掘出的规则进行分析和运用。就业信息数据实验证明，文中所提方法对就业信息进行挖掘是有效的、可行的。
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| 关 键 词： | 数据挖掘 量化关联规则 k—means聚类算法 就业信息 |
Application of Quantitative Association Rules in College Employment Information Data |
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| ZHANG Xiao-ping,ZHU Yu-quan,CHEN Geng. Application of Quantitative Association Rules in College Employment Information Data[J]. Computer Technology and Development, 2013, 0(11): 199-202,212 |
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| Authors: | ZHANG Xiao-ping ZHU Yu-quan CHEN Geng |
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| Affiliation: | 1. College of Computer Science ＆ Telecommunications Engineering, Jiangsu University, Zhenjiang 212013, China; 2. College of Information Science,Nanjing Audit University,Nanjing 210029, China) |
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| Abstract: | In view of the phenomenon such as a lot of quantitative attributes and categorical attributes among the employment information data,proposed an algorithm for mining quantitative association rules based on k-means. This method uses k-means clustering algorithm to partition the quantitative attributes reasonably and convert quantitative attributes to Boolean type;use the improved Boolean association rules method to conduct mining association rules on this to find the correlation between student＇ s educational attributes and employment attributes;analyze and apply the rules. Employment information data experimental results show that the presented method is effective and feasible in mining the employment information data. |
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| Keywords: | data mining quantitative association rules k-means clustering algorithm employment information |
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