Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/7735
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dc.contributor.authorManoj, Kumar, M.V.
dc.contributor.authorThomas, L.
dc.contributor.authorAnnappa, B.
dc.date.accessioned2020-03-30T10:02:43Z-
dc.date.available2020-03-30T10:02:43Z-
dc.date.issued2015
dc.identifier.citationCEUR Workshop Proceedings, 2015, Vol.1371, January, pp.132-143en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/7735-
dc.description.abstractConcept drift is the condition when the process changes during the course of execution. Current methods and analysis techniques existing in process mining are not proficient of analyzing the process which has experienced the concept drift. State-of-the-art process mining approaches consider the process as a static entity and assume that process remains same from beginning of its execution period to end. Emphasis of this paper is to propose the technique for localizing concept drift in control-flow perspective by making use of activity correlation strength feature extracted using process log. Concept drift in the process is localized by applying statistical hypothesis testing methods. The proposed method is verified and validated on few of the real-life and artificial process logs, results obtained are promising in the direction of efficiently localizing the sudden concept drifts in process-log.en_US
dc.titleCapturing the sudden concept drift in process miningen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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