help研究问题移动传感与用户行为预测建模如何在语言和文化边界上,开发和验证一种多维度的技术亲和力(Technology Affinity)测量工具?CHI '25The TAEG Questionnaire: Assessing Individual Affinity for Technology Across Different Countries
help研究问题移动传感与用户行为预测建模技术亲和力的四个维度(技术热情、技术能力、自我评估、技术正面和负面影响)如何受到年龄、性别和国家的影响?CHI '25The TAEG Questionnaire: Assessing Individual Affinity for Technology Across Different Countries
help研究问题移动传感与用户行为预测建模多语言版本的TAEG问卷能否有效预测个人的技术使用时间和经验水平?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
help研究问题移动传感与用户行为预测建模能否通过整合已安装应用数据和上下文信息改善用户行为预测的性能?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
help研究问题移动传感与用户行为预测建模如何利用大语言模型(LLMs)自动生成移动传感策略以支持人类行为建模?UbiComp '24Leveraging Large Language Models for Generating Mobile Sensing Strategies in Human Behavior Modeling
help研究问题移动传感与用户行为预测建模大语言模型能否通过多粒度的行为表示机制提升移动传感策略生成的效率和通用性?UbiComp '24Leveraging Large Language Models for Generating Mobile Sensing Strategies in Human Behavior Modeling
help研究问题移动传感与用户行为预测建模如何系统化地推荐数据源、特征构建方法以及机器学习模型以满足具体的研究目标?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
help研究问题移动传感与用户行为预测建模智能手机基于日常活动(S-ADL)方法能否有效检测使用者的血液酒精浓度(BAC)?CHI '24S-ADL: Exploring Smartphone-based Activities of Daily Living to Detect Blood Alcohol Concentration in a Controlled Environment
help研究问题移动传感与用户行为预测建模哪些智能手机交互任务最敏感地反映酒精对认知功能的轻微影响?CHI '24S-ADL: Exploring Smartphone-based Activities of Daily Living to Detect Blood Alcohol Concentration in a Controlled Environment
help研究问题移动传感与用户行为预测建模基于智能手机交互数据的机器学习模型在BAC检测中的准确性如何?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
help研究问题移动传感与用户行为预测建模如何通过智能手机数据预测电动汽车用户的出发时间(充电终止时间)以优化充电管理?UbiComp '23Departure Time Prediction Using Smartphone Data for Delayed-Full Charging BMS Algorithm
help研究问题移动传感与用户行为预测建模行为特征是否比基于位置变化的运动模式分析更有效地预测用户出发时间?UbiComp '23Departure Time Prediction Using Smartphone Data for Delayed-Full Charging BMS Algorithm
help研究问题移动传感与用户行为预测建模使用Delayed-Full Charging算法能否在减少电池退化的同时确保行驶续航范围不受影响?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
help研究问题移动传感与用户行为预测建模如何利用智能手机日志提取用户自身服务和竞品服务的使用行为特征进行用户流失预测?UbiComp '23Stay Ahead of the Competition: An Approach for Churn Prediction by Leveraging Competitive Service App Usage Logs
help研究问题移动传感与用户行为预测建模竞品服务使用行为的哪些特征最能提升不同类型应用的流失预测模型的表现?UbiComp '23Stay Ahead of the Competition: An Approach for Churn Prediction by Leveraging Competitive Service App Usage Logs
help研究问题移动传感与用户行为预测建模竞品服务的使用行为特征在不同应用类别(如“音乐与音频”、“娱乐”)中的预测效果有何差异?UbiComp '23Stay Ahead of the Competition: An Approach for Churn Prediction by Leveraging Competitive Service App Usage Logs
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
help研究问题移动传感与用户行为预测建模如何解决当前基于摄像头的无接触生理测量模型在不同域数据中泛化能力差的问题?UbiComp '22MobilePhys: Personalized Mobile Camera-Based Contactless Physiological Sensing
help研究问题移动传感与用户行为预测建模双摄像头系统(使用智能手机的前置和后置摄像头)能否提升个性化无接触生理测量的准确性?UbiComp '22MobilePhys: Personalized Mobile Camera-Based Contactless Physiological Sensing
help研究问题移动传感与用户行为预测建模通过自监督伪标签生成能否在不依赖高质量标注数据的情况下提高模型性能?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
help研究问题移动传感与用户行为预测建模手机传感技术能否有效跟踪第一代大学生第一年中的行为和心理健康动态变化?UbiComp '22First-Gen Lens: Assessing Mental Health of First-Generation Students across Their First Year at College Using Mobile Sensing
help研究问题移动传感与用户行为预测建模第一代大学生的行为模式与心理健康指标之间存在哪些具体关联?UbiComp '22First-Gen Lens: Assessing Mental Health of First-Generation Students across Their First Year at College Using Mobile Sensing
help研究问题移动传感与用户行为预测建模深度学习模型如何改善第一代大学生心理健康预测的精度并解决样本偏差问题?UbiComp '22First-Gen Lens: Assessing Mental Health of First-Generation Students across Their First Year at College Using Mobile Sensing
lightbulb现实痛点移动传感与用户行为预测建模第一代大学生因适应能力弱,心理健康风险高,易面临辍学威胁。UbiComp '22First-Gen Lens: Assessing Mental Health of First-Generation Students across Their First Year at College Using Mobile Sensing
help研究问题移动传感与用户行为预测建模智能手机LiDAR传感器能否通过激光散斑分析准确检测液体的黏度特性?UbiComp '22Detecting Liquid Properties Using Smartphone LiDAR Sensors
help研究问题移动传感与用户行为预测建模如何设计算法应对LiDAR调制和iPhone滚动快门效应以提取液体信息?UbiComp '22Detecting Liquid Properties Using Smartphone LiDAR Sensors
help研究问题移动传感与用户行为预测建模智能手机LiDAR技术在医学血液检测和食品质量控制中能否提供实用性和稳定性?UbiComp '22Detecting Liquid Properties Using Smartphone LiDAR Sensors
lightbulb现实痛点移动传感与用户行为预测建模患者和食品从业者难以低成本检测液体特性。UbiComp '22Detecting Liquid Properties Using Smartphone LiDAR Sensors
help研究问题移动传感与用户行为预测建模如何在不需要手动标注的情况下,从智能手机音频数据中检测自然呼吸的吸气和呼气阶段?UbiComp '21BreathTrack: Detecting Regular Breathing Phases from Unannotated Acoustic Data Captured by a Smartphone
help研究问题移动传感与用户行为预测建模知识迁移(teacher-student 模型)能否提高基于音频的呼吸相位检测的准确性?UbiComp '21BreathTrack: Detecting Regular Breathing Phases from Unannotated Acoustic Data Captured by a Smartphone
help研究问题移动传感与用户行为预测建模如何在干扰背景噪声的条件下实现自然呼吸音的精确分段和标注?UbiComp '21BreathTrack: Detecting Regular Breathing Phases from Unannotated Acoustic Data Captured by a Smartphone
lightbulb现实痛点移动传感与用户行为预测建模用户通过智能手机监测呼吸相位时,难以准确应对背景噪声和复杂场景。UbiComp '21BreathTrack: Detecting Regular Breathing Phases from Unannotated Acoustic Data Captured by a Smartphone