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Conference Papers Year : 2010

Detecting Anomalies in Data Streams using Statecharts (Demo)

Abstract

The environment around us is progressively equipped with various sensors, producing data continuously. The applications using these data face many challenges, such as data stream integration over an attribute (such as time) and knowledge extraction from raw data. In this paper we propose one approach to face those two challenges. First, data streams integration is performed using statecharts which represents a resume of data produced by the corresponding data producer. Second, we detect anomalous events over temporal relations among statecharts. We describe our approach in a demonstration scenario, that is using a visual tool called Patternator.
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Dates and versions

hal-01381632 , version 1 (14-10-2016)

Identifiers

  • HAL Id : hal-01381632 , version 1

Cite

Vasile-Marian Scuturici, Dan-Mircea Suciu, Romain Vuillemot, Aris Ouksel, Lionel Brunie. Detecting Anomalies in Data Streams using Statecharts (Demo). Extraction et Gestion des Connaissances (EGC'10), Jan 2010, Hammamet, Tunisie. pp.635-636. ⟨hal-01381632⟩
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