Naslov
Automated Decision-Making with DMN: from Decision Trees to Decision Tables

Autori
Etinger, Darko ; Simić, Srđan Daniel ; Buljubašić, Lea

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics / Skala, Karolj - Rijeka : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2019, 1514-1518

Skup
42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2019)

Mjesto i datum
Opatija, Hrvatska, 20.05.2019. - 24.05.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Business Process Management (BPM) ; Decision Model and Notation (DMN) ; decision trees

Sažetak
Recent advances in artificial intelligence, especially the subfield of machine learning, is commonly cited as one of the driving forces for digital transformation and innovative business models. Ongoing research is focusing on embedding solutions based on machine learning into business processes which are commonly modelled using the BPMN standard. The Object Management Group has recently adopted the Decision Model and Notation standard. By using the Decision Model and Notation (DMN) it is possible to replace multiple decision points embedded in business processes. The purpose of this research is to provide a method to derive DMN decision tables from the corresponding machine learning model generated by the decision tree classifier. The development is conducted using the Python machine learning library scikit-learn and Camunda Modeler. This approach facilitates and automates the process of converting machine learning models into DMN tables.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti

POVEZANOST RADA