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Data mining technology in Wah College Student Employment Analysis Research
Author: LiJinHua
Tutor: ZhaoHuiQun；QianZhenGuo
School: North China University of
Course: Computer Science and Technology
Keywords: Association algorithm Decision Tree Algorithm Career Guidance Data Mining
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 71
Quote: 0
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Abstract
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In college enrollment policy under the influence of the number of students in colleges and universities continue to expand, which gives university administrators and management models put forward higher requirements, so the colleges and universities have adopted the digital and information management tool. Such as teaching management information system, student elective system, management information systems and other student employment at major colleges and universities has been widely used. With the increasing number of students have graduated, graduate underlying database data accumulated more and more hidden depths of these data in the data surface of some of our managers can not observe important information. In this paper, Beijing Technology and Business University School of previous graduates Jiahua data as the mining objects, use of data mining techniques from Beijing Technology and Business University graduates based database Jiahua extract implicit, unknown knowledge. Data mining techniques to predict the future development trend of things and behaviors that can appear between the results appear to have hidden data and contact so that we can make some advance knowledge-driven decisions. In mining algorithms, data mining association rules is currently one of the main mode of study, focusing on the data to determine the relationship between the different areas, identify satisfy the given support and confidence thresholds dependencies between multiple domains relationship. However, if only based on the original Apriori algorithm for multidimensional association rule mining will generate a lot of candidate frequent itemsets. At present, many to summarize the number of rule-based system is the basis of dig digging decision tree induction method, so this article with a mining association rules mining and ID3 two algorithms. Application of decision tree induction algorithm to generate decision tree, the decision tree from the root to the leaf nodes of a path on the formation of the corresponding object class prediction. In these categories forecasts as the basis for a strong association rules and then get a valid result, decision tree algorithm can clearly indicate which field is more important, more intuitive information to explore the link between the students. Graduates data using decision tree algorithms for data mining is to identify the main factors affecting student employment, while looking for ways to help Beijing Technology and Business University Wah School (Independent Institute) graduates an effective way to help improve graduate employment guidance on effectiveness, while changing the method of employment guidance, training mode and lesson plans to meet the market demand, improve students' employment rate. After a large number of graduates of data mining, found that students of comprehensive results, English, thesis results, practice good marks a move into the state economy will be the type of units, in addition to comprehensive results can be seen, English achievement, graduation paper grades, social practices, and male students score better choice of party members Postgraduate likely. Finally, the results of data mining and the use of the students 'education and teaching management, with emphasis on cultivating students' English, professional knowledge and social practice, to meet the market demand for the community to train qualified personnel.
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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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