Knowledge Discovery Process Through Process Mining

The main goal of process mining is to extract semantic knowledge from process execution traces for the purposes of process understanding, innovation and improvement. In this paper we describe a leading process model for a knowledge discovery process and metadata knowledge discovery process. Normally the knowledge can be developed or generated with various process models. Hence the new proposed process model can help to discover new decision or process method or control system for the industry experts or process controllers. Therefore, this paper deals about that how to create an event log and create a mined process model. The process mining is an emerging technology used to generate event logs from input data. Hence we demonstrated the event log for an automobile repair business process. So, the data stored in the database can be effectively analyze and discover the knowledge for various activities of automobile repair process. This paper demonstrates a metadata of an automobile repair process using process mining tools such as ProM framework by ProM mining framework Incorporation. The metadata such as Extensible Markup Language (XML) or Mining Extensible Markup Language (MXML) script is mostly accepted by process mining tools to generate a new mined process model for the better process management or discovery of knowledge for any type of applications. Hence, this paper also deals about the leading process mining algorithm and metadata standards based on XML and MXML.