An Approach to Evaluate the Local Completeness of an Event Log
Process mining links traditional model-driven Business Process Management and data mining by means of deriving knowledge from event logs to improve operational business processes. As an impact factor of the quality of process mining results, the degree of completeness of the given event log should b...
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Published in | 2012 IEEE 12th International Conference on Data Mining pp. 1164 - 1169 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.12.2012
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Subjects | |
Online Access | Get full text |
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Summary: | Process mining links traditional model-driven Business Process Management and data mining by means of deriving knowledge from event logs to improve operational business processes. As an impact factor of the quality of process mining results, the degree of completeness of the given event log should be necessarily measured. In this paper an approach is proposed in the context of mining control-flow dependencies to evaluate the local completeness of an event log without knowing any information about the original process model. Experiment results show that the proposed approach works robustly and gives better estimation than approaches available. |
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ISBN: | 1467346497 9781467346498 |
ISSN: | 1550-4786 2374-8486 |
DOI: | 10.1109/ICDM.2012.66 |