SHA-SCP: A UI Element Spatial Hierarchy Aware Smartphone User Click Behavior Prediction Method
Year: 2025
Type: article
Abstract: Predicting user click behavior and making relevant recommendations based on the user’s historical click behavior are critical to simplifying operations and improving user experience. Modeling User Interface (UI) elements is essential to user click behavior prediction, while the complexity and variety of the UI make it difficult to adequately capture the information of different scales. In addition, the lack of relevant datasets also presents difficulties for such studies. In response to these challenges, we construct a fine-grained smartphone usage behavior dataset containing 3 664 325 clicks of 100 users and propose a UI elementSpatialHierarchyAwareSmartphone userClick behaviorPrediction method (SHA-SCP). SHA-SCP builds element groups by clustering the elements according to their spatial positions and uses attention mechanisms to perceive the UI at the element level and the element group level to fully capture the information of different scales. Experiments are conducted on the fine-grained smartphone usage behavior dataset, and the results show that our method outperforms the best baseline by an average of 18.35$\%$, 13.86$\%$, and 11.97$\%$in Top-1 Accuracy, Top-3 Accuracy, and Top-5 Accuracy, respectively.
Authors: Ling Chen, Qian Chen, Yiyi Peng, Kai Qian, Hongyu Shi, Xiaofan Zhang
Institution: Zhejiang University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Award: G1583088338
OpenAlex ID: W4414008378