Eye-tracking for Intelligent Personalization of Information Visualization

用户自适应交互是人工智能（AI）和人机交互（HCI）的交叉领域，旨在创建智能交互系统，通过实时建模和适应相关用户的需求和能力，为用户提供个性化的交互体验。用户自适应交互的好处已经在各种任务和应用中得到了证明（Jameson 2009）。该提案通过调查用户自适应交互的新应用领域来支持该领域前沿的研究：用户自适应可视化 *Infovis变得越来越重要，因为应用程序的持续增长允许 不仅在专业设置中，而且在个人使用中（例如，监测健身，跟踪社交媒体中的互动，了解家庭资源消耗（Huang et al. 2015）。到目前为止，可视化通常是基于要处理的任务和数据的类型来设计的，而不考虑用户的差异。然而，越来越多的证据表明，可视化效果取决于用户的特定偏好，能力，状态，甚至个性。本提案中要求的眼动跟踪设备将有助于研究如何创建可视化，该可视化可以从用户如何看待它们来推断相关用户的特征，并相应地个性化可视化，以最好地满足用户的需求和能力。**

User-adaptive interaction, a field at the intersection of artificial intelligence (AI) and human-computer interaction (HCI), aims to create intelligent interactive systems that provide users with a personalized interaction experience by modelling and adapting in real-time to relevant users' needs and abilities. The benefits of user-adaptive interaction have been shown for a variety of tasks and applications (Jameson 2009). This proposal supports research at the forefront of this field by investigating a new domain of application for user-adaptive interaction: user-adaptive visualizations***Infovis is becoming increasingly important given the continuous growth of applications that allow users to view and manipulate complex data, not only in professional settings, but also for personal usage (e.g., monitoring fitness, tracking interactions in social media, understanding home resources consumption (Huang et al. 2015). To date, visualizations are typically designed based on the type of tasks and data to be handled, without taking into account user differences. However, there is mounting evidence that visualization effectiveness depends on a user's specific preferences, abilities, states, and even personality. The eye-tracking equipment requested in this proposal will be instrumental to investigate how to create visualizations that can infer the relevant user's characteristics from how users look at them, and personalized the visualization accordingly, to best suit the users needs and abilities. **