The age of big data is now coming. But the traditional data analytics may not be able to
handle such large quantities of data. The question that arises now is, how to develop a high …

The development and application of data mining algorithms requires the use of powerful
software tools. As the number of available tools continues to grow, the choice of the most …

It is already true that Big Data has drawn huge attention from researchers in information
sciences, policy and decision makers in governments and enterprises. As the speed of …

The practical relevance of process mining is increasing as more and more event data
become available. Process mining techniques aim to discover, monitor and improve real …

Recent breakthroughs in process mining research make it possible to discover, analyze, and
improve business processes based on event data. The growth of event data provides many …

Most data mining approaches assume that the data can be provided from a single source. If
data was produced from many physically distributed locations like Wal-Mart, these methods …

Recent developments in sensor networks and mobile computing led to a huge increase in
data generated that need to be processed and analyzed efficiently. In this context, many …

In this paper, we present several considerations centered around the data-driven system
approaches. We briefly explore three main issues: the evolving relationship between off-line …

Process discovery—discovering a process model from example behavior recorded in an
event log—is one of the most challenging tasks in process mining. Discovery approaches …

As the size of available datasets has grown from Megabytes to Gigabytes and now into
Terabytes, machine learning algorithms and computing infrastructures have continuously …