Infrequent Behaviour Filtering From Business Process Event Logs
Journal Title: BEST : International Journal of Management, Information Technology and Engineering ( BEST : IJMITE ) - Year 2019, Vol 7, Issue 7
Abstract
Among all recent technologies “Big Data” has the capability to deal or analyze with the bulk amount of both structured and unstructured data. Analysis of a particular type of data is called "Process mining" (i.e, the data resulted after the execution of specified business processes).Examine the resulted output from process mining had created a negative impact, due to the presence of outliers. Because of the presence of outliers in the resulted output, “noise” or “infrequent behavior” produced. The main objective of the process discovery is automatically extracting the process models from discovered data; which may lead a result of rarely traveled pathways that fill process models. The proposed idea to present an online-based automated technique which intern will remove infrequent behavior from business process event logs. The application which is proposed on recent process discovery algorithms will significantly reform the discovered process models to a better extend and it scales well to huge data-sets.
Authors and Affiliations
Priyadharshini K, Gayathri G
Keywords
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