Process mining is widely used to diagnose processes and uncover performance compliance problems. It also possible see relations between different behavioral aspects, e.g., cases that deviate more at the beginning of process tend get delayed in later part process. However, correlations do not necessarily reveal causalities. Moreover, standard diagnostics indicate how improve This reason we advoc...

In this paper, we present a literature survey of Process Mining and its identified implementation. The aim is the identification most prom­inent Critical Success Factors that should be achieved for successful pro­cess mining We concluded with ten proposed critical suc­cess factors assessed in any process also elaborate on role business manage­ment contribution resolving drawbacks.

The article describes the basic principles and methods of Data mining and Process mining, their similarities and differences. The authors examine the research in Educational Data Mining field, associated with the use of Data mining techniques in education, give examples of problems to be solved with the use of Data mining and Process mining techniques in the area of traditional and e-learning, ...

Recently, several large companies have been involved in financial scandals related to mismanagement, resulting in financial damages for their stockholders. In response, certifications and manuals for best practices of governance were developed, and in some cases, tougher federal laws were implemented (e.g. the Sarboness Oxley Act). Companies adhered to these changes adopting the best practices ...

The management of business processes has recently received much attention, since it can support significant efficiency improvements in organizations. One of the most interesting problems is the description of a process model in a language, also equipped with an operational support, that allows checking the compliance of a process execution (trace) to the model. Another problem of interest is th...

Many known process mining techniques scale badly in the number of activities in an event log. Examples of such techniques include the ILP Miner and the standard replay, which also uses ILP techniques. To alleviate the problems these techniques face, we can decompose a large problem (with many activities) into a number of small problems (with few activities). Expectation is, that the run times o...

Process mining offers a way to distill process models from event logs originating from transactional systems in logistics, banking, e-business, health-care, etc. The algorithms used for process mining are complex and in practise large logs are needed to derive a high-quality process model. To support these efforts, the process mining tool EMiT has been built. EMiT is a tool that imports event l...