文章基本信息

标题：An ML-Powered Human Behavior Management System
本地全文：下载
作者：Sihem Amer-Yahia ; Reynold Cheng ; Mohamed Bouadi 等
期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2020
卷号：43
期号：3
页码：53-64
出版社：IEEE Computer Society
摘要：Our work aims to develop novel technologies for building an efficient data infrastructure as a backbone for a human behavior management system. Our infrastructure aims at facilitating behavior modeling, discovery, and exploitation, leading to two major outcomes: a behavior data management back-end and a high-level behavior specification API that supports mining, indexing and search, and AI-powered algorithms that provide the ability to extract insights on human behavior and to leverage data to advance human capital. We discuss the role of ML in populating and maintaining the back-end, and in exploiting it for human interest.