ndependently of the specific task to be enacted in a smart space, it is always crucial to mine a set of models representing environmental dynamics and, noteworthy, user habits, desires. Many different formalisms have been proposed to model human habits, but the vast majority of them are either difficult to read, evaluate or their definition requires a huge amount of work from either experts or users. In this paper we propose to employ process mining techniques in order to model human habits, we experimentally evaluate such an approach on a dataset built adopting the Smart-Home-in-a-Box toolkit with real users.

Process-Based Habit Mining: Experiments and Techniques / Dimaggio, Marcella; Leotta, Francesco; Mecella, Massimo; Sora, Daniele. - ELETTRONICO. - (2016), pp. 145-152. (Intervento presentato al convegno 13th IEEE International Conference on Ubiquitous Intelligence and Computing, 13th IEEE International Conference on Advanced and Trusted Computing, 16th IEEE International Conference on Scalable Computing and Communications, IEEE International Conference on Cloud and Big Data Computing, IEEE International Conference on Internet of People and IEEE Smart World Congress and Workshops tenutosi a Toulouse; France nel 18-21 July 2016) [10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0043].

Process-Based Habit Mining: Experiments and Techniques

Leotta Francesco
;
Mecella Massimo
;
Sora Daniele
2016

Abstract

ndependently of the specific task to be enacted in a smart space, it is always crucial to mine a set of models representing environmental dynamics and, noteworthy, user habits, desires. Many different formalisms have been proposed to model human habits, but the vast majority of them are either difficult to read, evaluate or their definition requires a huge amount of work from either experts or users. In this paper we propose to employ process mining techniques in order to model human habits, we experimentally evaluate such an approach on a dataset built adopting the Smart-Home-in-a-Box toolkit with real users.
2016
13th IEEE International Conference on Ubiquitous Intelligence and Computing, 13th IEEE International Conference on Advanced and Trusted Computing, 16th IEEE International Conference on Scalable Computing and Communications, IEEE International Conference on Cloud and Big Data Computing, IEEE International Conference on Internet of People and IEEE Smart World Congress and Workshops
Habit mining; Process mining; Smart home
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Process-Based Habit Mining: Experiments and Techniques / Dimaggio, Marcella; Leotta, Francesco; Mecella, Massimo; Sora, Daniele. - ELETTRONICO. - (2016), pp. 145-152. (Intervento presentato al convegno 13th IEEE International Conference on Ubiquitous Intelligence and Computing, 13th IEEE International Conference on Advanced and Trusted Computing, 16th IEEE International Conference on Scalable Computing and Communications, IEEE International Conference on Cloud and Big Data Computing, IEEE International Conference on Internet of People and IEEE Smart World Congress and Workshops tenutosi a Toulouse; France nel 18-21 July 2016) [10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0043].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/931939
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