| Autor: |
Wang, Jianmin, Wong, Raymond K., Ding, Jianwei, Guo, Qinlong, Wen, Lijie |
| Zdroj: |
2012 IEEE 19th International Conference on Web Services; 1/ 1/2012, p311-318, 8p |
| Abstrakt: |
While many process mining algorithms have been proposed recently, there does not exist a widely-accepted benchmark to evaluate and compare these process mining algorithms. As a result, it can be difficult to choose a suitable process mining algorithm for a given enterprise or application domain. Some recent benchmark systems have been developed and proposed to address this issue. However, evaluating available process mining algorithms against a large set of business models (e.g., in a large enterprise) can be computationally expensive, tedious and time-consuming. This paper proposes a novel framework that can efficiently select the process mining algorithms that are most suitable for a given model set. In particular, it attemptsto investigate how we can avoid evaluating numerous process mining algorithms on all given process models. [ABSTRACT FROM PUBLISHER] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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