利用自然语言处理的力量来批量生产测试项目

Martin C. Yu, Taylor Sullivan
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引用次数: 0

摘要

测试项目的大规模生产涉及许多步骤,需要时间。技术可以在补充人力资源方面发挥关键作用,无论是收集和存储原始材料,与主题专家交流,还是在复杂或快节奏的开发周期中同步和协调活动。我们在使用自然语言处理的自动项目生成(AIG)方面的工作就是这个过程在实践中展开的一个例子。在过去的几年中,激增的发展领域的自然语言理解和生成(NLU / NLG)关于应用程序开发的语言模型通过机器学习技术尚未应用于美国国际集团(AIG)的面积。我们向AIG介绍了NLU/NLG方法,并描述了我们在使该技术被更广泛的测试开发社区使用方面所做的努力。
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Harnessing the Power of Natural Language Processing to Mass Produce Test Items
Mass production of test items involves numerous steps and takes time. Technology can play a key role in supplementing human resources whether gathering and storing source materials, communicating with subject matter experts, or synchronizing and coordinating activities during a complex or fast-paced development cycle. Our work in automated item generation (AIG) using natural language processing is one example of this process unfolding in practice. Over the past few years, there has been a surge in developments in the fields of natural language understanding and generation (NLU/NLG) regarding applications of language models developed via machine learning techniques that have yet to be applied to the area of AIG. We introduce NLU/NLG approaches to AIG and describe our efforts in making the technology accessible to the broader test development community.
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