Streaming process mining refers to the set of techniques and tools which have the goal of processing a stream of data (as opposed to a finite event log). The goal of these techniques, similarly to their corresponding counterparts described in the previous chapters, is to extract relevant information concerning the running processes. This chapter presents an overview of the problems related to the processing of streams, as well as a categorization of the existing solutions. Details about control-flow discovery and conformance checking techniques are also presented together with a brief overview of the state of the art.
CITATION STYLE
Burattin, A. (2022). Streaming Process Mining. In Lecture Notes in Business Information Processing (Vol. 448, pp. 349–372). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-08848-3_11
Mendeley helps you to discover research relevant for your work.