[1]徐怡[][],陈玉莹[],赵彦娇[],等. 基于粗糙集理论的高校学生就业意向研究[J].计算机技术与发展,2015,25(10):209-213.
 XU Yi[] [],CHEN Yu-ying[],ZHAO Yan-jiao[],et al. Research on College Students’ Employment Intention Based on Rough Set Theory[J].,2015,25(10):209-213.
点击复制

 基于粗糙集理论的高校学生就业意向研究()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年10期
页码:
209-213
栏目:
应用开发研究
出版日期:
2015-10-10

文章信息/Info

Title:
 Research on College Students’ Employment Intention Based on Rough Set Theory
文章编号:
1673-629X(2015)10-0209-05
作者:
 徐怡[1][2] 陈玉莹[2] 赵彦娇[2] 乔春城[2]
 1.安徽大学 计算智能与信号处理教育部重点实验室;2.安徽大学 计算机科学与技术学院;3.安徽大学 计算机科学与技术学院
Author(s):
 XU Yi[1] [2]CHEN Yu-ying[2] ZHAO Yan-jiao[2] QIAO Chun-cheng[2]
关键词:
 粗糙集高校学生就业意向属性约简规则提取
Keywords:
 rough setemployment intention of college studentattribute reductionrule extraction
分类号:
TP301
文献标志码:
A
摘要:
 就业是高校学生学习的主要目标之一,由于影响学生就业意向的因素众多,导致学生不能清楚分析自己的就业意向,就业时存在盲目性。为了帮助高校学生准确分析自己的就业意向,文中首先设计了高校学生就业意向调查问卷表,面向本校大一至大四的学生分发调查问卷收集数据,然后利用粗糙集理论改进的基于分辨矩阵的属性约简算法,找出影响高校学生就业意向的关键因素,利用粗糙集理论改进的基于分辨矩阵的规则提取算法,挖掘影响高校学生就业意向的关键因素和就业意向之间的依赖关系,导出支持度高、泛化能力强的规则集,最后通过实验验证了规则集的有效性。研究成果可以帮助高校学生更清楚地分析自己的就业意向,指导学生做出更好的职业规划,为将来的就业提供帮助。
Abstract:
 Employment is one of the main goals of college students’ learning. Because there are many factors influencing the employment intention of students,students cannot clearly analyze their employment intention with blindness in employment. In order to help college students accurately analyze their employment intention,the college students’ employment intention survey questionnaire is designed,for freshman to senior student,distribute questionnaires to collect data. Improved attribute reduction algorithm based on discernibility matrix of rough set theory is used to find out the key factors affecting the employment intention of college students. Improved rule extraction al-gorithm based on discernibility matrix of rough set theory is employed to mine the dependence relation between the key factors impacting employment intention of college students and the employment intention. Rule sets with high support degree and strong generalization abili-ty are derived,and through the experiments,verify the effectiveness of rule sets. The research results can help college students analyze their employment intention more clearly,guiding students to make better career planning,and providing the help for future employment.

相似文献/References:

[1]夏奇思 王汝传.基于属性约简的粗糙集海量数据分割算法研究[J].计算机技术与发展,2010,(04):5.
 XIA Qi-si,WANG Ru-chuan.Mass Data Partition for Rough Set on Attribute Reduction Algorithm[J].,2010,(10):5.
[2]张政超 关欣[] 何友 李应升 郭伟峰.粗糙集理论数据处理方法及其研究[J].计算机技术与发展,2010,(04):12.
 ZHANG Zheng-chao,GUAN Xin[],HE You,et al.Rough Sets Data Processing Method and Its Research[J].,2010,(10):12.
[3]杨乐婵 邓松 徐建辉.基于BP网络的洪灾风险评价算法[J].计算机技术与发展,2010,(04):232.
 YANG Le-chan,DENG Song,XU Jian-hui.Flood Risk Evaluation Algorithm on BP Net[J].,2010,(10):232.
[4]张学友 苗强 毛军军.基于粗糙度的一种分形维数计算方法[J].计算机技术与发展,2010,(05):136.
 ZHANG Xue-you,MIAO Qiang,MAO Jun-jun.A Calculation Method of Fractal Dimension Based on Roughness[J].,2010,(10):136.
[5]王伟 高亮 吴涛.粗糙集在经济分析中的应用[J].计算机技术与发展,2008,(04):158.
 WANG Wei,GAO Liang,WU Tao.Application of Rough Set in Economic Analysis[J].,2008,(10):158.
[6]李学文 王小刚.优势信息系统的属性约简算法[J].计算机技术与发展,2009,(08):107.
 LI Xue-wen,WANG Xiao-gang.Algorithm on Attribute Reduction in Dominance Information System Based on Dominance Relation[J].,2009,(10):107.
[7]徐沈 吴涛[] 李国成.产业结构调整的量化分析[J].计算机技术与发展,2009,(08):178.
 XU Shen,WU Tao,LI Guo-cheng.Quantitative Analysis on Adjustment of Industrial Structure[J].,2009,(10):178.
[8]申锦标 吕跃进.粗糙集的近似约简及其算法[J].计算机技术与发展,2009,(12):17.
 SHEN Jin-biao,LU Yue-jin.A Rough Set of Approximate Attribute Reduction and Its Algorithm[J].,2009,(10):17.
[9]王小菊 蒋芸 李永华.基于依赖度之差的属性重要性评分[J].计算机技术与发展,2009,(01):67.
 WANG Xiao-ju,JIANG Yun,LI Yong-hua.Significance of Attribute Evaluation Based on Dependable Difference[J].,2009,(10):67.
[10]汪小燕 杨思春.基于改进的二进制可辨矩阵的核增量式更新方法[J].计算机技术与发展,2009,(01):97.
 WANG Xiao-yan,YANG Si-chun.An Incremental Updating Approach to Compute a Core Based on Improved Binary Discernable Matrix[J].,2009,(10):97.
[11]鄂旭[],杨健[],王欣铨[],等. 水产品安全信息系统中属性离散化方法研究[J].计算机技术与发展,2014,24(07):178.
 E Xu[],YANG Jian[],WANG Xin-quan[],et al. Research on Discretization Method in Aquatic Product Safety Information System[J].,2014,24(10):178.
[12]王添,姜麟,米允龙. 海量数据下不完备信息系统的知识约简算法[J].计算机技术与发展,2015,25(01):137.
 WANG Tian,JIANG Lin,MI Yun-long. Knowledge Reduction Algorithms of Incomplete Information System in Massive Datasets[J].,2015,25(10):137.
[13]胡来丰,舒兰. 基于粗集理论的决策树在信用卡发放中的应用[J].计算机技术与发展,2015,25(03):142.
 HU Lai-feng,SHU Lan. Application of Decision Tree Based on Rough Set Theory in Credit Card Payment[J].,2015,25(10):142.
[14]唐启涛,张燕,彭利红. 基于粗糙集约简算法的配置文本聚类方法研究[J].计算机技术与发展,2015,25(11):105.
 TANG Qi-tao,ZHANG Yan,PENG Li-hong. Research on Clustering Method of Configuration Text Based on Rough Sets Reduction Algorithm[J].,2015,25(10):105.
[15]闫之焕. Tableau算法在粗糙描述逻辑中的扩展应用[J].计算机技术与发展,2015,25(12):10.
 YAN Zhi-huan. Extension Application of Tableau Algorithm in Rough Description Logic[J].,2015,25(10):10.
[16]严静静,张腾飞. 基于自适应的粗糙C-均值聚类算法[J].计算机技术与发展,2016,26(03):67.
 YAN Jing-jing,ZHANG Teng-fei. Rough C-means Clustering Algorithm Based on Self-adaption[J].,2016,26(10):67.
[17]杨志勇,朱跃龙,万定生. 基于知识粒度的时间序列异常检测研究[J].计算机技术与发展,2016,26(07):51.
 YANG Zhi-yong,ZHU Yue-long,WAN Ding-sheng. Research on Time Series Anomaly Detection Based on Knowledge Granularity[J].,2016,26(10):51.
[18]蔡兴雨[],徐怡[][],程智炜[]. 基于粗糙集理论的影响高校学生成绩因素研究[J].计算机技术与发展,2016,26(11):200.
 CAI Xing-yu[],XU Yi[],CHENG Zhi-wei[]. Research on Factors Affecting College Achievement Based on Rough Set[J].,2016,26(10):200.

更新日期/Last Update: 2015-11-13