@inproceedings{50124ec626294dd980a5e2eeec270769,
title = "AGACY monitoring: A hybrid model for activity recognition and uncertainty handling",
abstract = "Acquiring an ongoing human activity from raw sensor data is a challenging problem in pervasive systems. Earlier, research in this field has mainly adopted data-driven or knowledge based techniques for the activity recognition, however these techniques suffer from a number of drawbacks. Therefore, recent works have proposed a combination of these techniques. Nevertheless, they still do not handle sensor data uncertainty. In this paper, we propose a new hybrid model called AGACY Monitoring to cope with the uncertain nature of the sensor data. Moreover, we present a new algorithm to infer the activity instances by exploiting the obtained uncertainty values. The experimental evaluation of AGACY Monitoring with a large real-world dataset has proved the viability and efficiency of our solution.",
keywords = "Machine learning, Ontology, Smart home, Uncertainty",
author = "Hela Sfar and Amel Bouzeghoub and Nathan Ramoly and J{\'e}r{\^o}me Boudy",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 14th Extended Semantic Web Conference, ESWC 2017 ; Conference date: 28-05-2017 Through 01-06-2017",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-58068-5\_16",
language = "English",
isbn = "9783319580678",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "254--269",
editor = "Diana Maynard and Aldo Gangemi and Rinke Hoekstra and Eva Blomqvist and Olaf Hartig and Pascal Hitzler",
booktitle = "The Semantic Web - 14th International Conference, ESWC 2017, Proceedings",
}