  Process Mining is a famous technique which is frequently applied to Software
Development Processes, while being neglected in Human-Computer Interaction
(HCI) recommendation applications. Organizations usually train employees to
interact with required IT systems. Often, employees, or users in general,
develop their own strategies for solving repetitive tasks and processes.
However, organizations find it hard to detect whether employees interact
efficiently with IT systems or not. Hence, we have developed a method which
detects inefficient behavior assuming that at least one optimal HCI strategy is
known. This method provides recommendations to gradually adapt users' behavior
towards the optimal way of interaction considering satisfaction of users. Based
on users' behavior logs tracked by a Java application suitable for
multi-application and multi-instance environments, we demonstrate the
applicability for a specific task in a common Windows environment utilizing
realistic simulated behaviors of users.
