An ML-Powered Human Behavior Management System

Sihem Amer-Yahia (1) , Reynold Cheng (2) , Mohamed Bouadi (3) , Abdelouahab Chibah (1) , Mohammadreza Esfandiari (3) , Jiangping Zhou (2) , Nan Zhang (2) , Eric Lau (2) , Yuguo Li (2) , Xiaolin Han (2) , Shivansh Mittal (2)

1 LIG - Laboratoire d'Informatique de Grenoble
2 HKU - The University of Hong Kong
3 UGA - Université Grenoble Alpes

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.

Domaines: Informatique [cs]

Sihem Amer-Yahia, Reynold Cheng, Mohamed Bouadi, Abdelouahab Chibah, Mohammadreza Esfandiari, et al.. An ML-Powered Human Behavior Management System. Bulletin of the Technical Committee on Data Engineering, 2020, 43 (3), pp.53-64. ⟨hal-02991027⟩