Toolkit to support intelligibility in context-aware applications
Toolkit to support intelligibility in context-aware applications
复制标题
支持上下文感知应用程序的清晰度的工具包
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
A. Dey
中科院分区：
文献类型：
--
作者：
Brian Y. Lim;A. Dey
情景感知应用程序应该是易懂的，这样用户才能更好地了解它们的工作方式，并提高他们对它们的信任。然而，提供可理解性并不是一件容易的事，它要求开发人员了解如何从应用程序决策模型生成解释。此外，用户需要不同类型的解释，这使得可理解性的实现变得复杂。我们开发了可理解性工具包，使应用程序开发人员可以轻松地从最流行的上下文感知应用程序决策模型中获得八种类型的解释。我们描述了它的可扩展体系结构，以及我们开发的解释生成算法。我们通过使用该工具包为最终用户生成解释的三个规范应用程序来验证该工具包的有用性。
Context-aware applications should be intelligible so users can better understand how they work and improve their trust in them. However, providing intelligibility is non-trivial and requires the developer to understand how to generate explanations from application decision models. Furthermore, users need different types of explanations and this complicates the implementation of intelligibility. We have developed the Intelligibility Toolkit that makes it easy for application developers to obtain eight types of explanations from the most popular decision models of context-aware applications. We describe its extensible architecture, and the explanation generation algorithms we developed. We validate the usefulness of the toolkit with three canonical applications that use the toolkit to generate explanations for end-users.