Maggi, Fabrizio Mari, juhendajaShikhizada, AladdinTartu Ülikool. Loodus- ja täppisteaduste valdkondTartu Ülikool. Arvutiteaduse instituut2023-11-072023-11-072020https://hdl.handle.net/10062/94083Most companies are deeply concerned about monitoring their business processes. It has special importance for them because in this way they can detect and avoid undesired outcome that can happen. In this context, prescriptive process monitoring techniques aim at analyzing historical behavior of business processes recorded in event logs using machine learning algorithms and then use this information for providing recommendations about actions to take in ongoing process executions to achieve a desired outcome. In this research, our goal is to build a process-oriented recommender system by implementing two approaches for prescriptive process monitoring. The system takes an event log as input, builds a predictor based on the information retrieved from the log and use it for providing recommendations on validation data.engopenAccessAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Predictive Process MonitoringPrescriptive Process MonitoringProcess MiningDeclarative process modelsProcess discoveryConformance checkingRecommender systemsmagistritöödinformaatikainfotehnoloogiainformaticsinfotechnologyThesis