Intellectual Behaviour of Student Based on Education Data Determined by Opinion Mining

M. N, J. S
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引用次数: 1

Abstract

Every student has individual thought process which make them unique and intelligent in their own way. Intellectual behaviour is a relation between thoughts, learning and knowledge. This paper focus on Students' feedback which is crucial for an institution to evaluate intellectual behavior of student. Opinion Mining (OM) deals with classifying and identifying opinion expressed by the students. The requirement of OM is to understand and analyse dissimilar behaviour of different personality which is a collection of extracted information from various resources. A solution to analyse cognitive behaviour of students based on the OM is a Natural Language Processing (NLP) and task of extracting information which discovers user's opinion interpreted in terms of positive or negative comments. The OM has played an important role in cognizing the emotional and intellectual behavior of university student through social media which may either be accomplished with viable or untenable education. Machine Learning (ML) algorithm helps to find the accuracy of polarity present in the OM. The Support Vector Machine (SVM) has shown better accuracy which is 93% through OM on the analysis of intellectual behavior for the student based on their knowledge and learning methodology.
基于意见挖掘教育数据的学生智力行为研究
每个学生都有自己独特的思维过程,这使他们以自己的方式变得独特和聪明。智力行为是思想、学习和知识之间的一种关系。学生的反馈是学校评估学生智力行为的关键。意见挖掘(OM)是对学生表达的意见进行分类和识别。OM的要求是理解和分析不同人格的不同行为,这是从各种资源中提取的信息的集合。基于OM分析学生认知行为的一种解决方案是自然语言处理(NLP)和提取信息的任务,该任务发现用户的意见被解释为积极或消极的评论。OM在通过社交媒体认识大学生的情感和智力行为方面发挥了重要作用,这可以通过可行或不可行的教育来完成。机器学习(ML)算法有助于找到OM中存在的极性的准确性。基于学生的知识和学习方法,支持向量机(SVM)通过OM对学生的智力行为进行分析,显示出更好的准确率,达到93%。
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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