@inproceedings{zhang2022predicting,
	title = {Predicting Next Actions and Latent Intents during Text Formatting},
	author = {Guanhua Zhang and Susanne Hindennach and Jan Leusmann and Felix B\"{u}hler and Benedict Steuerlein and Sven Mayer and Mihai B\^{a}ce and Andreas Bulling},
	year = {2022},
	booktitle = {Proceedings of the CHI Workshop Computational Approaches for Understanding, Generating, and Adapting User Interfaces},
	pages = {1--6},
	url = {https://sven-mayer.com/wp-content/uploads/2022/08/zhang2022predicting.pdf},
	date = {2022-01-01},
	abstract = {In this work we investigate the challenging task of predicting user intents from mouse and keyboard input as well as gaze behaviour. In contrast to prior work we study intent prediction at two different resolutions on the behavioural timeline: predicting future input actions as well as latent intents to achieve a high-level interaction goal. Results from a user study (N=15) on a sample text formatting task show that the sequence of prior actions is more informative for intent prediction than gaze. Only using the action sequence, we can predict the next action and the high-level intent with an accuracy of 66% and 96%, respectively. In contrast, accuracy when using features extracted from gaze behaviour was significantly lower, at 41% and 46%. This finding is important for the development of future anticipatory user interfaces that aim to proactively adapt to user intents and interaction goals.},
	keywords = {user intent prediction, text formatting, anticipatory user interfaces, mouse and keyboard input, gaze behavior, high-level interaction goals, input action prediction, latent intents}
}