Data Mining of Students' Response on the University Services using Chi-square Automatic Interaction Detector (CHAID) Algorithm

Maryli F. Rosas, Shaneth C. Ambat, Melvin A. Ballera
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引用次数: 1

Abstract

Students' insights are very vital in the continuous quality improvement of a university. Students are the primary consumers in higher education institution services [1].One way to measure the quality of education is through the satisfaction level of the students based on students' overall university experience. Implementation of logistic regression and CHAID Algorithm was used to create the recommendation plan.Text analytics was integrated to extract key phrases and compute sentiment score to classify the comments according to satisfaction level.
基于卡方自动交互检测器(CHAID)算法的学生对大学服务响应的数据挖掘
学生的真知灼见对大学质量的持续提升至关重要。学生是高校服务的主要消费者[1]。衡量教育质量的一种方法是根据学生的整体大学经历来衡量学生的满意度。采用logistic回归和CHAID算法创建推荐计划。结合文本分析提取关键短语并计算情感评分,根据满意度对评论进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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