Modeling Knowledge Bases for Automated Decision Making Systems – A Literature Review
Modeling Knowledge Bases for Automated Decision Making Systems – A Literature Review
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DOI：
10.14569/ijacsa.2015.060925
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发表时间：
2015-12
影响因子：
0.9
通讯作者：
F. Füßl;Detlef Streitferdt;Anne Triebel
中科院分区：
文献类型：
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作者：
F. Füßl;Detlef Streitferdt;Anne Triebel
开发自动化决策系统意味着以各种可能的方式处理知识。开发人工智能系统最重要的一点是开发具有集成自学习机制的精确知识库。此外，在专家系统或决策支持系统中使用知识，有必要记录知识并使其可见以进行管理。本工作的主要目标是为自动化决策系统中的知识库建模找到一个合适的解决方案，该解决方案涉及说明特定的知识和学习机制。有很多不同的术语描述这类研究，如知识建模、知识工程或本体工程。出于这个原因，本文提供了一个比较的专业术语在这一领域通过说明相似性，特殊性和如何使用他们在文学。
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.