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Article

Development of Knowledge Base Using Human Experience Semantic Network for Instructive Texts

1
Faculty of Energy Systems and Nuclear Science, Ontario Tech University, Oshawa, ON L1G 0C5, Canada
2
Department of Electrical and Computer Engineering, Ontario Tech University, Oshawa, ON L1G 0C5, Canada
3
IRI, Reactor Innovation, Ontario Power Generation, Whitby, ON L1N 9E3, Canada
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Jesualdo Tomás Fernández Breis
Appl. Sci. 2021, 11(17), 8072; https://doi.org/10.3390/app11178072
Received: 2 July 2021 / Revised: 20 August 2021 / Accepted: 22 August 2021 / Published: 31 August 2021
An organized knowledge structure or knowledge base plays a vital role in retaining knowledge where data are processed and organized so that machines can understand. Instructive text (iText) consists of a set of instructions to accomplish a task or operation. Hence, iText includes a group of texts having a title or name of the task or operation and step-by-step instructions on how to accomplish the task. In the case of iText, storing only entities and their relationships with other entities does not always provide a solution for capturing knowledge from iTexts as it consists of parameters and attributes of different entities and their action based on different operations or procedures and the values differ for every individual operation or procedure for the same entity. There is a research gap in iTexts that created limitations to learn about different operations, capture human experience and dynamically update knowledge for every individual operation or instruction. This research presents a knowledge base for capturing and retaining knowledge from iTexts existing in operational documents. From each iTexts, small pieces of knowledge are extracted and represented as nodes linked to one another in the form of a knowledge network called the human experience semantic network (HESN). HESN is the crucial component of our proposed knowledge base. The knowledge base also consists of domain knowledge having different classified terms and key phrases of the specific domain. View Full-Text
Keywords: knowledge base; entity relationship extraction; natural language processing; human experience semantic network; knowledge structure knowledge base; entity relationship extraction; natural language processing; human experience semantic network; knowledge structure
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MDPI and ACS Style

Gabbar, H.A.; Jabar, S.S.A.; Hassan, H.A.; Ren, J. Development of Knowledge Base Using Human Experience Semantic Network for Instructive Texts. Appl. Sci. 2021, 11, 8072. https://doi.org/10.3390/app11178072

AMA Style

Gabbar HA, Jabar SSA, Hassan HA, Ren J. Development of Knowledge Base Using Human Experience Semantic Network for Instructive Texts. Applied Sciences. 2021; 11(17):8072. https://doi.org/10.3390/app11178072

Chicago/Turabian Style

Gabbar, Hossam A., Sk S.A. Jabar, Hassan A. Hassan, and Jing Ren. 2021. "Development of Knowledge Base Using Human Experience Semantic Network for Instructive Texts" Applied Sciences 11, no. 17: 8072. https://doi.org/10.3390/app11178072

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