48 citations · 87 across the 6 of their papers we have counts for
6 papers
DiversityOne: A Multi-Country Smartphone Sensor Dataset for Everyday Life Behavior Modeling
Matteo Busso, Andrea Bontempelli, Leonardo Javier Malcotti +23
Understanding everyday life behavior of young adults through personal devices, e.g., smartphones and smartwatches, is key for various applications, from enhancing the user experien…
Complex Daily Activities, Country-Level Diversity, and Smartphone Sensing: A Study in Denmark, Italy, Mongolia, Paraguay, and UK
Karim Assi, Lakmal Meegahapola, William Droz +19
Smartphones enable understanding human behavior with activity recognition to support people's daily lives. Prior studies focused on using inertial sensors to detect simple activiti…
Generalization and Personalization of Mobile Sensing-Based Mood Inference Models: An Analysis of College Students in Eight Countries
Lakmal Meegahapola, William Droz, Peter Kun +24
Mood inference with mobile sensing data has been studied in ubicomp literature over the last decade. This inference enables context-aware and personalized user experiences in gener…
A Context Model for Personal Data Streams
Fausto Giunchiglia, Xiaoyue Li, Matteo Busso +1
We propose a model of the situational context of a person and show how it can be used to organize and, consequently, reason about massive streams of sensor data and annotations, as…
Lifelong Personal Context Recognition
Andrea Bontempelli, Marcelo Rodas Britez, Xiaoyue Li +5
We focus on the development of AIs which live in lifelong symbiosis with a human. The key prerequisite for this task is that the AI understands - at any moment in time - the person…
Streaming and Learning the Personal Context
Fausto Giunchiglia, Marcelo Rodas Britez, Andrea Bontempelli +1
The representation of the personal context is complex and essential to improve the help machines can give to humans for making sense of the world, and the help humans can give to m…