Enhancing Social Events with Smart Collaborative Environments

Catarina Silva, Tiago Ramalho, J. Barraca
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引用次数: 0

Abstract

Data obtained from the user interactions, especially in professional events, can be useful to build user profiles, as well as clusters and groups of interest, or even a dedicated Social Network (SN). These SNs enable forecasting the users' interest, further increasing the capability to plan and execute future events, or communication activities. In this work we describe EventosUA, an Information and Communications Technology (ICT) platform combining event, session and participant management, with profiling and indoor location techniques aiming to promote richer interaction, and allowing higher refinement in events organised in a academic and professional context. We also present the initial work on a novel Machine Learning (ML) to build a truly connected SN, derived from user interactions.
通过智能协作环境增强社交活动
从用户交互中获得的数据,特别是在专业事件中获得的数据,对于构建用户配置文件,以及感兴趣的集群和组,甚至是专用的社交网络(SN)都很有用。这些社交网站能够预测用户的兴趣,进一步提高计划和执行未来事件或交流活动的能力。在这项工作中,我们描述了eventtosua,这是一个信息和通信技术(ICT)平台,结合了事件,会议和参与者管理,以及旨在促进更丰富互动的分析和室内定位技术,并允许在学术和专业背景下组织的事件中进行更高的改进。我们还介绍了一种新的机器学习(ML)的初步工作,以建立一个真正连接的SN,源自用户交互。
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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