Simplified Business Process Model Mining Based on Structuredness Metric
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- @InProceedings{WeiDongZhao:2011:CIS,
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author = "WeiDong Zhao and Xi Liu and Anhua Wang",
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title = "Simplified Business Process Model Mining Based on
Structuredness Metric",
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booktitle = "Seventh International Conference on Computational
Intelligence and Security, CIS 2011",
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year = "2011",
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month = "3-4 " # dec,
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pages = "1362--1366",
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address = "Hainan, china",
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keywords = "genetic algorithms, genetic programming, control flow,
event logs, fitness function, process complexity
metric, process model acquisition, simplified business
process model mining, structuredness metric, tree-based
individual representation, business data processing,
data mining, trees (mathematics)",
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isbn13 = "978-1-4577-2008-6",
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DOI = "doi:10.1109/CIS.2011.303",
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size = "5 pages",
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abstract = "Process mining is the automated acquisition of process
models from event logs. Although many process mining
techniques have been developed, most of them focus on
mining models from the prospective of control flow
while ignoring the structure of mined models. This
directly impacts the understandability and quality of
mined models. To address the problem, we have proposed
a genetic programming (GP) approach to mining
simplified process models. Herein, genetic programming
is applied to simplify the complex structure of process
models using a tree-based individual representation. In
addition, the fitness function derived from process
complexity metric provides a guideline for discovering
low complexity process models. Finally, initial
experiments are performed to evaluate the effectiveness
of the method.",
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notes = "Also known as \cite{6128344}",
- }
Genetic Programming entries for
WeiDong Zhao
Xi Liu
Anhua Wang
Citations