The week's pick
Reseach Article
Integrating Arabic Open Information Extraction Model by Machine Learning to Extract Relation
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 186 - Number 14 |
| Year of Publication: 2024 |
| Authors: Sally M.A. Elmorsy, Mohamed Bahh Eldin Abdellatief |
10.5120/ijca2024923172
|
Sally M.A. Elmorsy, Mohamed Bahh Eldin Abdellatief . Integrating Arabic Open Information Extraction Model by Machine Learning to Extract Relation. International Journal of Computer Applications. 186, 14 ( Mar 2024), 30-35. DOI=10.5120/ijca2024923172
Abstract
In this paper, The Arabic text presents various difficulties, as text mining in Arabic is challenging due to its inflectional solid and derivational nature. The applications of Arabic information extraction are still in their early stages and require an improved approach to take advantage of its potential. Information extraction requires a general method that can work on the text regardless of its domain (e.g., biomedical, sport, economics, etc.) and capture all its information. Machine learning techniques have been applied to make information extraction systems more portable. Machine learning aims to develop algorithms to assist or replace domain experts in knowledge engineering situations. By using learning algorithms that rely on open information extraction to automate information retrieval processes such as document classification, the modeling can reduce the workload of information workers and minimize the inconsistencies introduced by human error, focusing on the research domain and problem.
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