大学生就业影响因素中基于粗糙集的智能数据分析方法
|
摘要
大学生就业形势越来越严峻,影响就业的因素众多,各因素对就业情况的影响并不相同,且相互之间存在关联性。基于粗糙集理论,提出大学生就业因素重要度的定量度量方法,建立基于粗糙集的智能数据分析模型,实验结果表明了新型方法的有效性,能够为大学生的在校学习和就业规划提供了重要指导,并为高校培养和企业招聘优秀大学生提供了决策支持。
The situation of college students' employment is increasingly serious. There are numerous factors influencing college students' employment. However,their influences are different,which are connected to each other. Based on rough set theory,a quantitative measurement method of the importance of college students' employment factors,is put forward,and an intelligent data analyzing model of college students' employment factors based on rough set is also established. The experimental results show that the new methods are effective,which provides important guidance for college students' studying on campus and employment planning,as well as offers decision supports for university workers cultivating and corporation recruiting excellent college students.
The situation of college students' employment is increasingly serious. There are numerous factors influencing college students' employment. However,their influences are different,which are connected to each other. Based on rough set theory,a quantitative measurement method of the importance of college students' employment factors,is put forward,and an intelligent data analyzing model of college students' employment factors based on rough set is also established. The experimental results show that the new methods are effective,which provides important guidance for college students' studying on campus and employment planning,as well as offers decision supports for university workers cultivating and corporation recruiting excellent college students.
引文
[1]张常新.大学生就业质量的影响因素及对策[J].继续教育研究,2016(1):113-114.
[2]张斌,蒋怀滨,王叶飞,等.大学生就业焦虑影响因素及对策研究[J].教育教学论坛,2015(28):3-4.
[3]刘洋.高校大学生就业困难的因素与对策分析[J].淮北职业技术学院学报,2016(2):32-33.
[4]陆广峰.高校大学生就业难因素分析及对策研究[J].中国成人教育,2015(14):57-59.
[5] Macaro E. Strategies for language learning and for language use:Revising the theoretical framework[J]. The Modern Language Journal,2006(3):320-337.
[6]周章明,曾鸿鹄,王敦球.基于全面质量观的大学生就业质量评估指标体系构建探析[J].当代教育理论与实践,2012(11):43-45.
[7]段明秀.基于PSO优化的模糊RBF神经网络学习算法及其应用[J].当代教育理论与实践,2010(1):101-104.
[8]唐贡如,吴莉.独立学院大学英语教改探析——多媒体教学与基于多元智能理论差异教学的结合[J].当代教育理论与实践,2014(11):110-111.
[9]邹新月,周志强.产业结构视角下大学生就业困境与对策研究[J].当代教育理论与实践,2010(5):98-101.
[10]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(11):105-109.
[11] Pawlak Z. Rough sets[J]. International Journal of Computer and Information Science,1982(5):341-256
[12]苗夺谦,李道国.粗糙集理论、算法与应用[M].北京:清华大学出版社,2008.
[13]王国胤.Rough集理论与知识获取[M].西安:西安交通大学出版社,2001.
[14] Pickering M J,Garrod S. Toward a mechanistic psychology of dialogue[J]. Behavioral&Brain Sciences,2004(2):169-190.
[15]张文修,吴伟志,梁吉业,等.粗糙集理论与方法[M].北京:科学出版社,2001.
[16]Chen L S,Wang J Y(eds.). The Models of Granular System and Algebraic Quotient Space in Granular Computing[J]. Chinese Journal of Electronics,2016(6):1109-1113.
[17]Chen L S,Wang J Y(eds.). Quotient space model based on algebraic structure[J]. High Technology Letters,2016(2):160-169.
[18] Chen L S,Wang J Y. The rough representation and measurement of quotient structure in algebraic quotient space model[J]. High Technology Letters,2017(3):293-297.
[19]Chen L S,Wang J Y,Li L. A new granular computing model based on algebraic structure[J]. Chinese Journal of Electronics,2019(1):136-142.
[20]陈林书,柳媛慧.P2P网络中基于节点能力自适应的搜索算法[J].湖南科技大学学报(自然科学版),2009(2):61-65.
[2]张斌,蒋怀滨,王叶飞,等.大学生就业焦虑影响因素及对策研究[J].教育教学论坛,2015(28):3-4.
[3]刘洋.高校大学生就业困难的因素与对策分析[J].淮北职业技术学院学报,2016(2):32-33.
[4]陆广峰.高校大学生就业难因素分析及对策研究[J].中国成人教育,2015(14):57-59.
[5] Macaro E. Strategies for language learning and for language use:Revising the theoretical framework[J]. The Modern Language Journal,2006(3):320-337.
[6]周章明,曾鸿鹄,王敦球.基于全面质量观的大学生就业质量评估指标体系构建探析[J].当代教育理论与实践,2012(11):43-45.
[7]段明秀.基于PSO优化的模糊RBF神经网络学习算法及其应用[J].当代教育理论与实践,2010(1):101-104.
[8]唐贡如,吴莉.独立学院大学英语教改探析——多媒体教学与基于多元智能理论差异教学的结合[J].当代教育理论与实践,2014(11):110-111.
[9]邹新月,周志强.产业结构视角下大学生就业困境与对策研究[J].当代教育理论与实践,2010(5):98-101.
[10]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(11):105-109.
[11] Pawlak Z. Rough sets[J]. International Journal of Computer and Information Science,1982(5):341-256
[12]苗夺谦,李道国.粗糙集理论、算法与应用[M].北京:清华大学出版社,2008.
[13]王国胤.Rough集理论与知识获取[M].西安:西安交通大学出版社,2001.
[14] Pickering M J,Garrod S. Toward a mechanistic psychology of dialogue[J]. Behavioral&Brain Sciences,2004(2):169-190.
[15]张文修,吴伟志,梁吉业,等.粗糙集理论与方法[M].北京:科学出版社,2001.
[16]Chen L S,Wang J Y(eds.). The Models of Granular System and Algebraic Quotient Space in Granular Computing[J]. Chinese Journal of Electronics,2016(6):1109-1113.
[17]Chen L S,Wang J Y(eds.). Quotient space model based on algebraic structure[J]. High Technology Letters,2016(2):160-169.
[18] Chen L S,Wang J Y. The rough representation and measurement of quotient structure in algebraic quotient space model[J]. High Technology Letters,2017(3):293-297.
[19]Chen L S,Wang J Y,Li L. A new granular computing model based on algebraic structure[J]. Chinese Journal of Electronics,2019(1):136-142.
[20]陈林书,柳媛慧.P2P网络中基于节点能力自适应的搜索算法[J].湖南科技大学学报(自然科学版),2009(2):61-65.