Professional Identity Modeling and Optimization based on Collaborative Filtering Algorithm

被引:0
|
作者
Zhang, Xueping [1 ]
机构
[1] Wuhan City Vocat Coll, Wuhan 430064, Hubei, Peoples R China
来源
PROCEEDINGS OF 2017 9TH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA) | 2017年
关键词
preschool education; undergraduate professional identity; neural network; collaborative filtering; Matlab;
D O I
10.1109/ICMTMA.2017.53
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
with the diversification of education and the depth of integration of education and economy, the role of various professional supports for the social economy becomes more and more obvious. As a basic professional, preschool education has been a hot research area in various research teams and government education departments. How to carry on the objective reality, the comprehensive evaluation to the student professional identity, is a major problem which is placed in front of the scientific research personnel. The collaborative filtering algorithm based on neural network optimization, classical statistical methods integration, through the model self-learning; solve the sparsity of the judgment matrix, and evaluation index of comprehensive and objective of problem. By introducing the machine learning algorithm, using Matlab to calculate, the important features of the data hidden behind the data mining, the establishment of a good robustness, high accuracy of the identification of the model.
引用
收藏
页码:191 / 194
页数:4
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