Incremental Mining of Processes with Loops
Incremental Mining of Processes with Loops
复制标题
带循环的流程增量挖掘
DOI：
10.1142/s0218213011000103
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发表时间：
2011-02
影响因子：
1.1
通讯作者：
Hui Ma
中科院分区：
文献类型：
--
作者：
Yong Tang;Lingkun Wu;Hui Ma
目前，大多数流程挖掘研究侧重于从整个日志中发现工作流模型。事实上，流程设计者可能拥有一个部分构建的模型，并且他们的先验知识对于流程挖掘也是有价值的信息。此外，该……（句子似乎不完整，最后一个单词“la”可能是错误输入）
Currently most researches in process mining focus on discovering a workflow model from an entire log. In fact, the process designers may have a partially built model and their prior knowledge is also valuable information to process mining. Besides, the large volume of log data makes the process mining a time-consuming job. It is better that the process mining be done in an incremental way. There are only a few methods that can incrementally mine a model, but they have their limitations such as incapability in handling loops or being intolerant to noise. On the other hand, loop mining is a challenging problem in process mining because the repeatedly executed tasks add complexity to the search for task precedence. This paper studies the problem of handling loops in process mining and proposes an improved incremental process mining method which supports loops. Experiments in the end show the feasibility and validity of the proposed method.
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影响因子：
3.7
作者：
Rozinat, A.;van der Aalst, W. M. P.
通讯作者：
van der Aalst, W. M. P.
DOI：
10.1016/j.datak.2005.02.006
发表时间：
2006
期刊：
Data Knowl. Eng.
影响因子：
--
作者：
Markus Hammori;J. Herbst;Niko Kleiner
通讯作者：
Markus Hammori;J. Herbst;Niko Kleiner
DOI：
10.1016/j.compind.2003.10.002
发表时间：
2004-04
期刊：
Comput. Ind.
影响因子：
--
作者：
J. Herbst;D. Karagiannis
通讯作者：
J. Herbst;D. Karagiannis
影响因子：
3.4
作者：
L. Wen;Jianmin Wang;Wil M.P. van der Aalst;Biqing Huang;Jiaguang Sun
通讯作者：
L. Wen;Jianmin Wang;Wil M.P. van der Aalst;Biqing Huang;Jiaguang Sun
DOI：
10.1016/j.compind.2003.10.004
发表时间：
2004-04
期刊：
Comput. Ind.
影响因子：
--
作者：
S. Pinter;M. Golani
通讯作者：
S. Pinter;M. Golani