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An Automatic Ontology Generation Framework with An Organizational Perspective

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Title:An Automatic Ontology Generation Framework with An Organizational Perspective
Authors:Elnagar, Samaa
Yoon, Victoria
Thomas, Manoj
Keywords:Knowledge Flow, Transfer, Sharing, and Exchange
automatic ontology
free text ontology
graph embedding
knowledge graph consistency
show 1 moreknowledge graphs
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Date Issued:07 Jan 2020
Abstract:Ontologies have been known for their powerful semantic representation of knowledge. However, ontologies cannot automatically evolve to reflect updates that occur in respective domains. To address this limitation, researchers have called for automatic ontology generation from unstructured text corpus. Unfortunately, systems that aim to generate ontologies from unstructured text corpus are domain-specific and require manual intervention. In addition, they suffer from uncertainty in creating concept linkages and difficulty in finding axioms for the same concept. Knowledge Graphs (KGs) has emerged as a powerful model for the dynamic representation of knowledge. However, KGs have many quality limitations and need extensive refinement. This research aims to develop a novel domain-independent automatic ontology generation framework that converts unstructured text corpus into domain consistent ontological form. The framework generates KGs from unstructured text corpus as well as refine and correct them to be consistent with domain ontologies. The power of the proposed automatically generated ontology is that it integrates the dynamic features of KGs and the quality features of ontologies.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/64339
ISBN:978-0-9981331-3-3
DOI:10.24251/HICSS.2020.597
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Knowledge and Innovation Management: Connecting Theory to Practice to Business Performance


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