Elgamal, Marwa and Abou-Kreisha, Mohamed and Abo Elezz, Reda Abo and Hamada, Salwa (2020) An Ontology-based Name Entity Recognition NER and NLP Systems in Arabic Storytelling. Al-Azhar Bulletin of Science, 31 (2). pp. 31-38. ISSN 2636-3305
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Abstract
Ontology is a descriptive model representing domain knowledge with robust specifications that solve interoperability between humans and machines. In this work, a practical methodology presented for Arabic Storytelling ontology construction for domain ontology extraction from unstructured Arabic story documents. However, the manual construction of ontologies is a time-consuming and challenging process. Still, ontology construction and learning, which extracts ontological knowledge from various data types automatically or semi-automatically, can overcome the bottleneck of knowledge acquisition. This paper intends to investigate the problem of automatically construct and build an Arabic storytelling ontology based on Arabic named entity recognition (NER) from unstructured story text. This paper presents a system designed based on Machine Learning (ML) approach. The system framework is a combination of five main stages: The first stage determines the requirement analysis—second document pre-processing using NLP tasks. The third is Conceptualization. The fourth stage is formal design and construction, and the final step is evaluation.
Item Type: | Article |
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Subjects: | Open Archive Press > Medical Science |
Depositing User: | Unnamed user with email support@openarchivepress.com |
Date Deposited: | 21 Mar 2024 04:32 |
Last Modified: | 21 Mar 2024 04:32 |
URI: | http://library.2pressrelease.co.in/id/eprint/1788 |