We connect the disciplines of contemporary neuroscience and psychological theories with the engineering science of information technology systems. Therefor our goal is to develop new, interesting concepts for tomorrows intelligent world. On of these project is our attempt to improve the heuristic miner in the field of process mining.
Process mining is a process management technique that allows for the analysis of business processes based on event logs. The basic idea is to extract knowledge from event logs recorded by an information system. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs.
"The Alpha(+/++) Algorithm aimes at reconstructing causality from a set of sequences of events. It was first put forward by van der Aalst, Weijters and Măruşter. Several extensions or modifications of it have since been presented, which will be listed below. Within the concept of the algorithm one takes a workflow log as input and results in a workflow net being constructed. It does so by examining causal relationships observed between tasks. For example, one specific task might always precede another specific task in every execution trace, which would be useful information. "
"The main motivation of the genetic algorithms (Eiben and Smith 2003) is to benefit from the global search that is performed by this kind of algorithms. Genetic algorithms are adaptive search methods that try to mimic the process of evolution. These algorithms start with an initial population of individuals. Every individual is assigned a fitness measure to indicate its quality. In our case, an individual is a possible process model and the fitness is a function that evaluates how well the individual is able to reproduce the behavior in the log. Populations evolve by selecting the fittest individuals and generating new indi- viduals using genetic operators such as crossover (combining parts of two or more individuals) and mutation (random modification of an individual)."
"The Heuristic Miner extends the alpha algorithm by consider the frequency of traces in the log. Heuristics miner can deal with noise, and can be used to express the main behavior. The Heuristics Miner Plugin mines the control flow perspective of a process model. To do so, it only considers the order of the events within a case. In other words, the order of events among cases isn't important. For instance for the log in the log file only the fields case id, time stamp and activity are considered during the mining. The timestamp of an activity is used to calculate these orderings."
"Social mining or rather the analysis of social interconnected relationships is one of the most interesting topics of todays world. When deriving roles and other organizational entities from the event log the focus is on the relation between people or groups of people and the process. Another perspective is not to focus on the relation between the process and individuals but on relations among individuals (or groups of individuals)." Facebook uses it, the NSA does, so whats about it?
The biggest advantage of the heuristic algorithm is also its main problem. The Threshold. By increasing the threshold we are able to remove instances with a low frequence. But we have to watch out because the threshold applies to the entire net and not single edges within it. Therefor, there is always the possibility to remove process relevant information by increasing the threshold and we try to handle this failure.
Just imagine we increase the threshold and kick out failover instances within the process. That would be the state of emergency.
The Preprocessing Stage indicates the major part in order to find the sibling model of our research instance. Here we are comparing the log against all logs in our archive with algorithms close to the predictable behavoiral analysis group. But instead of comparing behaviors we take a look at the activities in order to find relative ones. If we have a match, we will mark the congruent model.
During the Postprocessing Stage we are able to compare the results of our heuristic miner with the results of the preprocessing stage. If we increase the threshold we can compare in time against the congruent model if process relevant activities get kicked out. Therefor we are able to increase the threshold without loosing process relevant activities.
In order to create a strong archive for comparison with predictable analysis, we offer this SaaS to work on. calculations are done by our server cluster