Application Layer Operation Intention Recognition Based on Mouse Behavior
Shiyuan Li, Hongfeng Niu, Jiading Chen, Zhongmin Cai · 2023
In today's rapidly advancing field of artificial intel-ligence, there is an increasing reliance on computers to recognize and understand our intentions. However, accurately recognizing and fulfilling user intention is a challenging task. This work pro-poses to address this challenge by investigating mouse behavior data. Through the collection and analysis of mouse behavior data, intention recognition experiments are conducted using machine learning and deep learning methods. The results demonstrate that visual representation methods outperform others in application-level intent recognition, achieving a highest recognition accuracy of 99.9%. This research highlights the significance of mouse behavior in intention recognition and provides empirical support for delivering personalized intelligent services. It bears crucial implications for the development of artificial intelligence and enhancing user experience.