多输出职业预测:数据集,方法和基准套件

Shruti Singh, Abhijeet Gupta, S. Baraheem, Tam V. Nguyen
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引用次数: 0

摘要

本文主要研究个体对未来职业道路的预测。这有利于行业中的各种应用,包括加强人力资源、职业指导和跟踪未来趋势。为此,我们通过LinkedIn网络收集了一个数据集,其中包含了每个人的工作职位和工作领域。每个人都有许多与历史背景相关的属性。在职业生涯预测方面,我们研究了六种不同的多类别多输出分类方法。通过基准套件,最佳分类器对工作领域和工作位置的准确率分别达到91.21%和95.97%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Output Career Prediction: Dataset, Method, and Benchmark Suite
In this paper, we investigate the career path prediction of an individual in the future. This benefits a variety of application in the industry including enhancing human resources, career guidance, and keeping track of future trends. To this end, we collected a dataset via LinkedIn network, with the job position and the job domain for each individual. There are many attributes related to historical background for each individual. For the career prediction, we investigate six different multi-class multi-output classification methods. Via the benchmark suite, the best classifier achieves an accuracy rate of 91.21% and 95.97% for the job domain and the job position, respectively.
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