Abstract
Recent advances in sensing techniques enabled the possibil- ity to gain precise information about switched-on devices in smart home environments. One is particularly interested in exploring different pat- terns of electrical usage of indoor appliances and using them to predict activities. This in turns results with many useful applications like in- ferring effective energy saving procedures. The necessity to derive this knowledge in the real time and the huge size of generated data initiated the need for a precise stream sequential pattern mining approach. Most available approaches are less accurate due to their batch-based nature. We present a smart home application of the PBuilder algorithm which uses a batch-free approach to mine sequential patterns of a real dataset collected from appliances. Additionally, we present the StrPMiner which uses the PBuilder to find sequential patterns within multiple streams. We show through an extensive evaluation over a smart home real dataset the superiority of the StrPMiner algorithm over a state-of-the-art approach.
Original language | English |
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Title of host publication | Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB. FGDB. Trier, Germany, October 7-9, 2015 |
Editors | R. Bergmann, S. Görg, G. Müller |
Publisher | CEUR-WS.org |
Pages | 159-170 |
Number of pages | 12 |
Publication status | Published - 2015 |
Externally published | Yes |
Event | LWA 2015 Workshops: KDML, FGWM, IR, and FGDB. FGDB. Trier, Germany, October 7-9 - University of Trier, Trier, Germany Duration: 7 Oct 2015 → 9 Oct 2015 http://lwa2015.wi2.uni-trier.de/ |
Publication series
Name | CEUR workshop Proceedings |
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Volume | 1458 |
ISSN (Electronic) | 1613-0073 |
Conference
Conference | LWA 2015 Workshops: KDML, FGWM, IR, and FGDB. FGDB. Trier, Germany, October 7-9 |
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Abbreviated title | LWA2015 |
Country/Territory | Germany |
City | Trier |
Period | 7/10/15 → 9/10/15 |
Internet address |