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Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Elina Sukhanova
Machine Learning and Quantum Probability Theory for Business Process Management
Business Informatics
(Bachelor’s programme)
2018
Nowadays, many business processes are highly dependent on the behavior of one subject. The person is the most important part of the intellectual business process, because they need to make decisions during the process, which can greatly affect the entire system of business processes. However, people's behavior is unpredictable, which leads to a number of risks, such as fraud, abuse of authority and others. Some scientists believe that it is impossible to predict human actions only in the classical probability theory, whereas in the quantum probability theory human behavior is logical and rational. In this case, it is possible to build a model which can predict what kind of decision a person would take in a particular situation, using machine learning algorithms and quantum probability theory.

The purpose of this work is to study the methods of machine learning and quantum probability theory for managing business processes. In this work the scientific literature on the topic of research is analyzed and a machine learning algorithm, automating the decision-making process in the business process of " credit issuing ", is built.

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