Abstract
Event logs constitute a rich source of information for several process analysis activities, which can take advantage of similar traces retrieval. The capability of relating semantic structures such as taxonomies to actions in the traces can enable trace comparison to work at different levels of abstraction and, therefore, to mask irrelevant details, and make the identification of similar traces much more flexible. In this paper, we propose a trace abstraction mechanism, which maps actions in the log traces to instances of ground concepts in a taxonomy, and then allows to generalize them up to the desired level. We also show how we have extended a trace similarity metric we defined in our previous work, in order to allow abstracted trace comparison as well. Our framework has been tested in the field of stroke management, where it has allowed us to cluster similar traces, corresponding to correct medical behaviors, abstracting from details, but still preserving the capabilities of identifying outlying situations.
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Montani, S., Striani, M., Quaglini, S., Cavallini, A., Leonardi, G. (2017). Semantic Trace Comparison at Multiple Levels of Abstraction. In: Aha, D., Lieber, J. (eds) Case-Based Reasoning Research and Development. ICCBR 2017. Lecture Notes in Computer Science(), vol 10339. Springer, Cham. https://doi.org/10.1007/978-3-319-61030-6_15
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