Career Prediction Model Using Data Mining and Linear Classification
Career Prediction Model Using Data Mining and Linear Classification
复制标题
使用数据挖掘和线性分类的职业预测模型
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Sudhir N. Dhage
中科院分区：
文献类型：
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作者：
R. Rangnekar;K. Suratwala;S. Krishna;Sudhir N. Dhage
当一个人决定一份职业时，这个选择可以完全塑造他的生活。最近，越来越多的人开始重新评估自己的职业决定，并在人生的后期转行。这可以通过在青少年开始研究生学习之前对他们进行适当的咨询来防止。为了解决这一问题，利用现有学生的数据，将个性、能力和学生一般信息信息与他们的职业进行映射。创建的直观职业系统使用了学生必须回答的各种问题来测试他们的能力，以及学生的背景问题。学生的个性是通过Facebook Graph API使用他们的社交媒体账户来确定的。然后，答案被输入到创建的模型中，以预测与学生的能力和个性相匹配的职业。该模型对能力、个性和背景信息的平均准确率分别为77.41%、75.4%和60.09%。这是一种现实的咨询方法，因为它同时考虑了个性和能力，这两个因素对职业决定负有责任。
When one decides a career, this choice can shape ones life entirely. Recently, more and more people have begun to re-evaluate their career decisions and change careers at a later stage in life. This can be prevented by proper counselling of young teenagers before they begin their graduate studies. To solve this problem, data of existing students is used, where the personalities, aptitude and student general information information is mapped with their careers. The created Intuitive Career System uses a variety of questions that students have to answer to test their aptitude as well as students background questions. The students personalities are determined using their social media accounts by means of the Facebook Graph API. The answers are then entered into the created model to predict the career that matches the students aptitude and personality. The model gives an average accuracy of 77.41% for the aptitude, 75.4% for personality, and 60.09% for the background information. This is a realistic approach to counselling since it takes into account both personality and aptitude, which are responsible for career decisions.