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Accelerating Model Driven Platforms: A study into the predictability of business process models

Tuininga, Frits Sieds (2019) Accelerating Model Driven Platforms: A study into the predictability of business process models.

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Abstract:In the modern business world, communication between distinct business units is in general achieved by the means of multiple computer systems. In some cases, these systems cannot communicate directly. Hence, an additional program must be added to make communication possible. Typically, the construction of this program can take quite some time. eMagiz is a company which creates such programs by the means of a model-driven platform (which is also called eMagiz). This research explores the opportunities of reducing time spent on creating such a program in eMagiz. To reduce time spent on creating programs in a model-driven platform, an assistance tool is created. This assistance tool helps a user to create programs more e�ectively and e�ciently. The assistance tool is based on a thorough machine learning analysis, which is described in detail within this report. During this study the following research question is answered: How can user actions in a model-driven platform be predicted, with machine learning, to increase modelling speed with the help of an assistance tool?. This question is answered in two phases.
Item Type:Essay (Bachelor)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:54 computer science, 70 social sciences in general, 85 business administration, organizational science
Programme:Industrial Engineering and Management BSc (56994)
Link to this item:http://purl.utwente.nl/essays/79280
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