An Overview of Ontology Learning Process from Arabic Text | ||||
| The Egyptian Journal of Language Engineering | ||||
| Article 1, Volume 7, Issue 1, April 2020, Page 1-13 PDF (1.15 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ejle.2020.19841.1000 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Mariam Muhammed  1; Nesrine Azim2; Mervat Gheith3
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| 1Department of Information Systems and Technology, FGSSR, Cairo University, Egypt. | ||||
| 2Department of Information Systems and Technology, FGSSR, Cairo University, Egypt | ||||
| 3Department of Computer Science, FGSSR, Cairo University, Egypt. | ||||
| Abstract | ||||
| Ontology learning (OL) Plays an important role in many fields such as semantic web, Data Integration and Interoperability, Machine Translation, and Information Retrieval. The success of any of these fields depends on the quality of its ontologies. This paper presents a comprehensive survey of research on the Ontology Learning for Arabic texts. Most of the previous works focused on three main issues: extracting the terms, extracting the semantic relations, and building the ontology from the Arabic text. There are more of techniques and methods can be used for this process. In this paper, first we present the Arabic challenges that were reasons for developing few Arabic Ontology Learning systems. Second we make a research comparison based on the techniques used and their results. Third, we pointed limitations and comments of research works on Arabic Ontology Learning. Finally, we concluded the paper and outlined our future research direction in this area. | ||||
| Keywords | ||||
| Arabic Ontology Learning; Term Extraction; Semantic Relation Extraction | ||||
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