Abstract: Process mining is a process management system that analyzes business processes built on event logs. The knowledge is extracted from event logs by using knowledge retrieval techniques. The process mining algorithms are capable of automatically discovering models to provide details of all the events registered in some log traces provided as input. The theory of regions is a valuable tool in process discovery: it aims at learning a formal model (Petri nets) from a set of traces. The main objective of this paper is to propose improved hidden markov model algorithm. The experiment is done based on standard bench mark dataset HELIX and RALIC datasets. The performance of the proposed system is better than existing method.
Keywords: Process Mining, Process Discovery, Sequence Clustering, Hidden Markov Model, Helix and RALIC Dataset.
Title: Analysis of Process Mining Model Using Improved HMM
Author: V.Priyadharshini, Dr. A. Malathi
International Journal of Interdisciplinary Research and Innovations
ISSN 2348-1226 (online), ISSN 2348-1218 (print)
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