What are they Researching? Examining Industry-Based Doctoral Dissertation Research through the Lens of Machine Learning

Ion Freeman, Ashley Haigler, Suzanna E. Schmeelk, Lisa Ellrodt, Tonya Fields
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引用次数: 6

Abstract

This paper examines industry-based doctoral dissertation research in a professional computing doctoral program for full time working professionals through the lens of different machine learning algorithms to understand topics explored by full time working industry professionals. This research paper examines machine learning algorithms and the IBM Watson Discovery machine learning tool to categorize dissertation research topics defended at Pace University. The research provides insights into differences in machine learning algorithm categorization using natural language processing.
他们在研究什么?从机器学习的角度审视基于行业的博士论文研究
本文通过不同的机器学习算法,考察了全职工作专业人员的专业计算博士课程中基于行业的博士论文研究,以理解全职工作行业专业人员探索的主题。本研究论文考察了机器学习算法和IBM Watson Discovery机器学习工具,以对佩斯大学辩护的论文研究主题进行分类。该研究提供了使用自然语言处理的机器学习算法分类差异的见解。
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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