摘要
利用学生课程成绩,挖掘课程间的内在关联,合理设置执行计划,为人才培养方案的制定提供决策支持,有效提高人才培养质量。针对FP-growth算法中存在极大内存开销弊端问题,提出基于二维表存储事务,进而求出频繁1项集、频繁2项集和非频繁2项集,实现减少对数据库事务遍历、对FP树剪枝以及减少遍历FP树次数。以某校信管专业学生成绩为研究对象,对算法的改进效率进行验证。
With the students′curriculum achievements,we can excavate the internal relationship between the courses,set up the implementation plan reasonably,provide decision support for the formulation of the talent training program,and effectively improve the quality of talent training.In view of the problem of huge memory overhead in FP growth algorithm,this paper proposes to store transactions based on two-dimensional table,and then find frequent one item set,frequent two-item set,and non frequent two item set,to reduce the traversal of database transactions,the pruning of FP Tree and the traversal of FP tree.In this paper,the efficiency of the algorithm is verified by taking the achievement of the students majoring in information management as the research object.
作者
叶福兰
YE Fu-lan(School of Technology,Fuzhou University of International Studies and Trade,Fuzhou 350202,China)
出处
《科技和产业》
2020年第4期186-190,共5页
Science Technology and Industry
基金
福建省2017年高等学校创新创业教育改革试点专业-信息管理与信息系统(JFS2017001)
福建省本科高校重大教改项目—大数据背景下基于新文科建设的创新创业教育研究与实践(FBJG20190284)。
