The refined process mining framework contains a set of activities that use extracted information from event logs, discovered models and normative ones. Among these activities, we find those dealing with running events in a Structured Business Process (SBP) context, which are the Detect, the Predict and the Recommend activities. These three activities are nominated as an operational support system that aims at detecting deviations, predicting events and recommending actions. In this regard, operational support systems perform well on SBP while, it stills a challenging task for an Unstructured Business Process (UBP). This puts forward the difficulty of predicting events and recommending actions for UBP, because of its complex structure. In this context, simplification and structuring operations must be applied. Therefore, the intervention of other process mining activities is required for business process simplification and structuring. To this end, we present an operational support approach dealing with UBP, using the refined process mining framework activities.
The information retrieval system is a set of resources and tools that allow users to search for information in a given domain. This system permits users to perform their research according to their objectives in diverse ways producing different behaviors. Even users with the same objective may follow different paths and stand different sub-processes, which are introduced as self-defined Business Processes that vary in terms of structure, objective, and result. This puts forward the difficulty of obtaining and studying these user’s behaviors. This paper targets the problem of representing and managing self-defined business process variability. A special interest is given to the use of process mining to deal with this challenge. In this regard, a case study about citizens in interaction with the Electronic Administration is presented, to discover and manage variability of this process type. The main result is a set of recommendations to end users.
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