Abstract
Nowadays, more and more organizations describe their operations in terms of business processes. Consequently, it is common for organizations to have collections of hundreds or even thousands of business process models. This calls for techniques to quickly retrieve business process models that satisfy a given query. Some advanced techniques for querying a collection business process models exist. However, these techniques mainly focus on the expressive power of the query language, and performing an advanced business process query using these techniques can take considerable time. Consequently, querying a collection of models can take considerable time. To solve this problem, this paper proposes an efficient technique, using feature nets. Experiments show that on average the technique performs two orders of magnitude faster than existing techniques.
Keywords
- Business Process
- Basic Node
- Business Process Model
- Inverted Index
- Query Graph
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Yan, Z., Dijkman, R., Grefen, P. (2012). FNet: An Index for Advanced Business Process Querying. In: Barros, A., Gal, A., Kindler, E. (eds) Business Process Management. BPM 2012. Lecture Notes in Computer Science, vol 7481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32885-5_20
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DOI: https://doi.org/10.1007/978-3-642-32885-5_20
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