ABBYY Timeline is a leading process mining software with advanced process discovery & task mining capabilities for end-to-end business process visibility
IBM Process Mining helps customers to extract process data from business, identify automation opportunities, prioritize by impact, and fast-track implementation.
Data Mining is an iterative process where the mining process can be refined, and new data can be integrated to get more efficient results. Data Mining meets the requirement of effective, scalable and flexible data analysis. It can be considered as a natural evaluation of information technology. ...
such as data science, process control and metallurgy, IT, change management, and capability building. OptimusAI leverages a full portfolio of digital solutions that combines science, data, and experts to help mining and processing companies make data-driven decisions to improve productivity, throughput...
The general extraction process involves injecting a leaching agent called “lixiviant” into the ore body (below the water table), dissolving uranium bearing species in solution, recovering the uranium bearing solution (sometimes referred to as “pregnant solution”) to the surface by pumping the ...
时间戳相对来说比较简单,越精确越好,如果有每个process step的start time 和end time那最好,如果如果时间戳只能精确到天而不能精确到秒,那么只能人为定义一个event order,来确定如果不同的activities 在同一天发生,process graph会按照event order的顺序来显示。
You can use text mining tools to extract common activity names from this free-text information field in a pre-processing step and then apply process mining afterwards. Furthermore, after you have used process mining to discover and visualize process problems, you may be using data mining ...
The cleaning step is usually a projection of the log to consider only the data you are interested in. Thus, in this section we show how you can inspect and clean (or pre-process) an event log in ProM. Furthermore, we show how you can save the results of the cleaned log, so that ...
2. Section 3 provides an overview of process mining and discusses problems related to process discovery. Section 4 introduces the approach by using a real-life example. The first step of our approach is presented in Sect. 5. Here it is shown that there are various ways to construct a ...
1. Set the business objectives:This can be the hardest part of the data mining process, and many organizations spend too little time on this important step. Even before the data is identified, extracted or cleaned,data scientistsand business stakeholders can work together to define the precise ...