评估自然语言政策制定的协助

Kami Vaniea, Clare-Marie Karat, Joshua B. Gross, J. Karat, C. Brodie
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引用次数: 28

摘要

本文报告的研究的目标是调查策略作者对策略情况的变化进行描述的能力,以及编写高质量、完整的策略规则的能力,这些规则可以进行高精度的解析。作为这项研究的一部分,我们调查了我们可以帮助政策制定者撰写政策的方法。本文介绍了在自然语言策略编写界面中提供语法高亮显示的有效性的用户研究结果。虽然实验对象喜欢新的界面,但他们在书写规则时的准确性没有提高。我们根据用户在创作或修改策略时所经历的三个阶段创作过程来讨论我们的结果。我们描述了这个过程,讨论了我们的界面为什么和如何不能支持它,并就如何更好地支持这个过程向设计师提出建议。
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Evaluating assistance of natural language policy authoring
The goal of the research study reported here was to investigate policy authors' ability to take descriptions of changes to policy situations and author high-quality, complete policy rules that would parse with high accuracy. As a part of this research, we investigated ways in which we could assist policy authors in writing policies. This paper presents the results of a user study on the effectiveness of providing syntax highlighting in a natural language policy authoring interface. While subjects liked the new interface, they showed no improvement in accuracy when writing rules. We discuss our results in terms of a three phase authoring process that users move through when authoring or modifying policies. We describe this process, discuss why and how our interface failed to support it and make recommendations to designers on how to better support this process.
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