CC4Spark: Distributing event logs and big complex conformance checking problems
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/355643
Tipus de documentText en actes de congrés
Data publicació2021
EditorCEUR-WS.org
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement 4.0 Internacional
ProjecteMODELOS Y METODOS BASADOS EN GRAFOS PARA LA COMPUTACION EN GRAN ESCALA (AEI-TIN2017-86727-C2-1-R)
Abstract
Conformance checking is one of the disciplines that best exposes the power of process mining, since it allows detecting anomalies and deviations in business processes, helping to assess and improve the quality of these. This is an indispensable task, especially in Big Data environments where large amounts of data are generated, and where the complexity of the processes is increasing. CC4Spark enables companies to face this challenging scenario in twofold. First, it supports distributing conformance checking alignment problems by means of a Big Data infrastructure based on Apache Spark, allowing users to import, transform and prepare event logs stored in distributed data sources, and solve them in a distributed environment. Secondly, this tool supports decomposed Petri nets. This helps to noticeably reduce the complexity of the models. Both characteristics help companies in facing increasingly frequent scenarios with large amounts of logs with highly complex business processes. CC4Spark is not tied to any particular conformance checking algorithm, so that users can employ customised algorithms.
CitacióValencia, Á. [et al.]. CC4Spark: Distributing event logs and big complex conformance checking problems. A: International Conference on Business Process Management. "Proceedings of the best dissertation award, doctoral consortium, and demonstration & resources track at BPM 2021: co-located with 19th International Conference on Business Process Management (BPM 2021): Rome, Italy, September 6th to 10th, 2021". CEUR-WS.org, 2021, p. 136-140. ISSN 1613-0073.
ISSN1613-0073
Versió de l'editorhttp://ceur-ws.org/Vol-2973/paper_277.pdf
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