DEMO: FLARE: Federated Active Learning Assisted by Naming for Responding to Emergencies

Viyom Mittal, Mohammad Jahanian, K. Ramakrishnan
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Abstract

Name-based pub/sub allows for efficient and timely delivery of information to interested subscribers. A challenge is assigning the right name to each piece of content, so that it reaches the most relevant recipients. An example scenario is the dissemination of social media posts to first responders during disasters. We present FLARE, a framework using federated active learning assisted by naming. FLARE integrates machine learning and name-based pub/sub for accurate timely delivery of textual information. In this demo, we show FLARE’s operation.
演示:FLARE:通过命名辅助的联邦主动学习,以响应紧急情况
基于名称的发布/订阅允许向感兴趣的订阅者有效和及时地传递信息。一个挑战是为每条内容分配正确的名称,以便它到达最相关的收件人。一个示例场景是在灾难期间向第一响应者传播社交媒体帖子。我们提出了FLARE,这是一个通过命名辅助的联邦主动学习框架。FLARE集成了机器学习和基于名称的发布/订阅,以准确及时地传递文本信息。在这个演示中,我们展示FLARE的操作。
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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