Ontology Learning Applications of Knowledge Base Construction for Microelectronic Systems Information

Author:

Wawrzik Frank1,Rafique Khushnood Adil1ORCID,Rahman Farin1ORCID,Grimm Christoph1ORCID

Affiliation:

1. WG Design of Cyber-Physical System, TU Kaiserslautern, 67663 Kaiserslautern, Germany

Abstract

Knowledge base construction (KBC) using AI has been one of the key goals of this highly popular technology since its emergence, as it helps to comprehend everything, including relations, around us. The construction of knowledge bases can summarize a piece of text in a machine-processable and understandable way. This can prove to be valuable and assistive to knowledge engineers. In this paper, we present the application of natural language processing in the construction of knowledge bases. We demonstrate how a trained bidirectional long short-term memory or bi-LSTM neural network model can be used to construct knowledge bases in accordance with the exact ISO26262 definitions as defined in the GENIAL! Basic Ontology. We provide the system with an electronic text document from the microelectronics domain and the system attempts to create a knowledge base from the available information in textual format. This information is then expressed in the form of graphs when queried by the user. This method of information retrieval presents the user with a much more technical and comprehensive understanding of an expert piece of text. This is achieved by applying the process of named entity recognition (NER) for knowledge extraction. This paper provides a result report of the current status of our knowledge construction process and knowledge base content, as well as describes our challenges and experiences.

Funder

GENIAL! project with funding from the BMBF

EU ECSEL Joint Undertaking

partners’ national funding authorities BMBF

Publisher

MDPI AG

Subject

Information Systems

Reference48 articles.

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3. Wawrzik, F. (2022). Knowledge Representation in Engineering 4.0. [Doctoral Thesis, Technische Universität Kaiserslautern].

4. Dalecke, S., Rafique, K., Ratzke, A., Grimm, C., and Koch, J. (2022, January 24–26). SysMD: Towards “Inclusive” Systems Engineering. Proceedings of the 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS), Coventry, UK.

5. Wawrzik, F., and Lober, A. (2021, January 27). A Reasoner-Challenging Ontology from the Microelectronics Domain. Proceedings of the Semantic Reasoning Evaluation Challenge (SemREC 2021) Co-Located with the 20th International Semantic Web Conference (ISWC 2021), Virtual Event.

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