lightbulb现实痛点移动传感与用户行为预测建模智能手机摄像头的生理测量技术不够精准,难以适应个体差异。UbiComp '22MobilePhys: Personalized Mobile Camera-Based Contactless Physiological Sensing
lightbulb现实痛点移动传感与用户行为预测建模现有工具无法跨语言和文化准确评估个人对技术的接纳度。CHI '25The TAEG Questionnaire: Assessing Individual Affinity for Technology Across Different Countries
lightbulb现实痛点移动传感与用户行为预测建模移动端应用推荐常因用户数据缺乏而不够精准。UbiComp '24MAPLE: Mobile App Prediction Leveraging Large Language Model Embeddings
lightbulb现实痛点移动传感与用户行为预测建模研究者设计移动传感策略费时复杂,难以跨情境应用。UbiComp '24Leveraging Large Language Models for Generating Mobile Sensing Strategies in Human Behavior Modeling
lightbulb现实痛点移动传感与用户行为预测建模年轻用户缺乏便捷、实时的工具监测酒精摄入,易导致健康和安全风险。CHI '24S-ADL: Exploring Smartphone-based Activities of Daily Living to Detect Blood Alcohol Concentration in a Controlled Environment
lightbulb现实痛点移动传感与用户行为预测建模电动汽车用户担心高电池充满时间导致电池寿命缩短。UbiComp '23Departure Time Prediction Using Smartphone Data for Delayed-Full Charging BMS Algorithm
lightbulb现实痛点移动传感与用户行为预测建模用户可以轻松切换竞品服务,服务商难以及时识别流失风险。UbiComp '23Stay Ahead of the Competition: An Approach for Churn Prediction by Leveraging Competitive Service App Usage Logs