Validation and Optimization Framework for Indoor Navigation Systems Using User Comments in Spatial-Temporal Context
Validation and Optimization Framework for Indoor Navigation Systems Using User Comments in Spatial-Temporal Context
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DOI：
10.1109/access.2019.2951014
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发表时间：
2019
期刊：
影响因子：
3.9
通讯作者：
Yang Tao;A. Ganz
中科院分区：
文献类型：
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作者：
Yang Tao;A. Ganz
在本文中，我们介绍了第一个时空文本框架，可以方便验证和优化室内导航系统使用试验参与者连续记录的反馈。所提出的框架使我们能够确定具体的改进领域，如用户界面的哪一部分需要改变，在环境中的哪些领域需要修改的定位算法，和/或哪些指令应该得到改进。对这种系统的传统评价是基于在试用后以访谈和/或问卷调查的形式收集用户的反馈。这种形式的评价虽然必要和重要，但它提供了用户对系统看法的摘要。相比之下，所提出的框架提供了一个显着的改进，通过不断收集以下信息在时空背景下的试验过程中，细化用户反馈的分辨率：用户评论，用户界面交互，和导航指令。该框架包括以下四个主要组成部分：1）试验数据预处理; 2）评论文本分析; 3）空间/时间/指令分析;和4）结果可视化。我们介绍了一个案例研究，说明了使用的框架，使用PERCEPT室内导航系统的盲人和视障用户。
In this paper we introduce the first spatial-temporal-textual framework that can facilitate the validation and optimization of indoor navigation systems using trial participants continuously recorded feedback. The proposed framework enables us to pinpoint specific areas of improvement such as which part of the user interface requires changes, what areas in the environment necessitate modifications in the localization algorithm, and/or which instructions should be improved. Conventional evaluation of such systems is based on collecting users’ feedback after the trials in the form of interviews and/or questionnaires. This form of evaluation while necessary and important, it provides a summary of the users’ view of the system. In contrast, the proposed framework provides a significant improvement by refining the user feedback resolution by continuously collecting the following information in a spatial-temporal context during the trials: user comments, user interface interactions, and navigation instructions. The framework includes the following four main components: 1) trial data preprocessing; 2) comments textual analysis; 3) spatial/temporal/instructions analysis, and 4) results visualization. We introduce a case study that illustrates the use of the framework using PERCEPT indoor navigation system for blind and visually impaired users.