Abstract: Developing automated decision making systems means dealing with knowledge in every possible manner. One of the most important points of developing artificial intelligent systems is developing a precise knowledge base with integrating self-learning mechanisms. Moreover using knowledge in expert systems or decision support systems it is necessary to document knowledge and make it visible for managing it. Main goal of this work is finding a suitable solution for modeling knowledge bases in automated decision making systems concerning both illustrating specific knowledge and learning mechanisms. There are a lot of different terms describing this kind of research, such as knowledge modeling, knowledge engineering or ontology engineering. For that reason this paper provides a comparison of the technical terms in this domain by illustrating similarities, specifics and how they are used in literature.

Franz Felix Füssl, Detlef Streitferdt and Anne Triebel, “Modeling Knowledge Bases for Automated Decision Making Systems – A Literature Review” International Journal of Advanced Computer Science and Applications(IJACSA), 6(9), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060925

@article{Füssl2015,
title = {Modeling Knowledge Bases for Automated Decision Making Systems – A Literature Review},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060925},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060925},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {9},
author = {Franz Felix Füssl and Detlef Streitferdt and Anne Triebel}
}