Summary abstract for the 1st ACM international workshop on personal data meets distributed multimedia

V. Singh, Tat-Seng Chua, R. Jain, A. Pentland
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引用次数: 2

Abstract

Multimedia data are now created at a macro, public scale as well as individual personal scale. While distributed multimedia streams (e.g. images, microblogs, and sensor readings) have recently been combined to understand multiple spatio-temporal phenomena like epidemic spreads, seasonal patterns, and political situations; personal data (via mobile sensors, quantified-self technologies) are now being used to identify user behavior, intent, affect, social connections, health, gaze, and interest level in real time. An effective combination of the two types of data can revolutionize multiple applications ranging from healthcare, to mobility, to product recommendation, to content delivery. Building systems at this intersection can lead to better orchestrated media systems that may also improve users' social, emotional and physical well-being. For example, users trapped in risky hurricane situations can receive personalized evacuation instructions based on their health, mobility parameters, and distance to nearest shelter. This workshop bring together researchers interested in exploring novel techniques that combine multiple streams at different scales (macro and micro) to understand and react to each user's needs.
第一届ACM个人数据与分布式多媒体国际研讨会摘要
多媒体数据现在是在宏观、公共规模和个人规模上创建的。虽然最近已将分布式多媒体流(例如图像、微博和传感器读数)结合起来,以了解流行病传播、季节模式和政治局势等多种时空现象;个人数据(通过移动传感器、量化自我技术)现在被用于实时识别用户行为、意图、影响、社会关系、健康、凝视和兴趣水平。两种数据类型的有效组合可以彻底改变多个应用程序,从医疗保健、移动、产品推荐到内容交付。在这个交叉点建立系统可以带来更好的协调媒体系统,也可以改善用户的社交、情感和身体健康。例如,被困在危险飓风中的用户可以根据他们的健康状况、机动性参数和到最近避难所的距离收到个性化的疏散指示。本次研讨会汇集了对探索新技术感兴趣的研究人员,这些技术结合了不同尺度(宏观和微观)的多个流,以了解和响应每个用户的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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