Name
Abstract | ||
|---|---|---|
Under the global trend of modern quality education, the set of higher educational scholarship is aimed to reward the students who work hard both inside and outside class activities and achieve great success in kinds of academic competitions. At this time, with great emphasis by governments and outstanding construction on the educational infrastructure, the number of students in universities has been increasing dramatically. Meanwhile, during the development of the education in such a long period, universities generally accumulate a huge amount of the information concerned with the students. What the administrators always do to handle such information are merely storing, querying and doing some other basic manipulations instead of making full use of these data. For example, those manual evaluations of the educational scholarship always revolve around the rank of scholarship and the number of the students who are rewarded rather than analyzing the facts which can influence the achieving of the scholarship. As a result, the evaluation is apparently lack of fairness and efficiency. In this paper, based on C4.5 decision tree, a higher educational scholarship evaluation model is built. By using such algorithm, an efficient and fair scholarship evaluation system can be realized. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.procs.2019.04.027 | Procedia Computer Science |
Keywords | Field | DocType |
C4.5 Decision Tree,Scholarship Evaluation,Data Mining | Data science,Decision tree,Evaluation system,Scholarship,Computer science,Artificial intelligence,Machine learning | Conference |
Volume | Issue | ISSN |
151 | C | 1877-0509 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| X. Wang | 1 | 1 | 1.03 |
| Chang-yu Zhou | 2 | 1 | 0.69 |
| X. Xu | 3 | 3 | 2.54 |