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 …

Online conformance checking deals with finding discrepancies between real-life and
modeled behavior on data streams. The current state-of-the-art output of online conformance …

Conformance checking techniques are used to compute to what degree a process model
and real execution data correspond to each other. In recent years, alignments have proven …

The combination of machine learning techniques with process analytics like process mining
might even significantly elevate novel insights into time series data collections. To efficiently …

Conformance checking detects deviations in business process executions. An online
detection method is needed to give immediate response to anticipate possible impacts. The …

Conformance checking is a class of process mining techniques, which contrasts the
modeled behaviors with the observed behaviors of a process, to detect, locate and explain …

Conformance checking deals with collating modeled process behavior with observed
process behavior recorded in event data. Alignments are a state-of-the-art technique to …

Conformance checking techniques aim to collate observed process behavior with
normative/modeled process models. The majority of existing approaches focuses on …

Identifying anomalies in business processes is a challenge organizations face daily and are
critical for their operations' data flow, whether public or private. Most current techniques face …

The aim of streaming conformance checking is to find discrepancies between process
executions on streaming data and the reference process model. The state-of-the-art output …