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Reseach Article

Integrating Arabic Open Information Extraction Model by Machine Learning to Extract Relation

by Sally M.A. Elmorsy, Mohamed Bahh Eldin Abdellatief
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

@article{ 10.5120/ijca2024923172,
author = { Sally M.A. Elmorsy, Mohamed Bahh Eldin Abdellatief },
title = { Integrating Arabic Open Information Extraction Model by Machine Learning to Extract Relation },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2024 },
volume = { 186 },
number = { 14 },
month = { Mar },
year = { 2024 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number14/integrating-arabic-open-information-extraction-model-by-machine-learning-to-extract-relation/ },
doi = { 10.5120/ijca2024923172 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-03-29T00:41:18.889030+05:30
%A Sally M.A. Elmorsy
%A Mohamed Bahh Eldin Abdellatief
%T Integrating Arabic Open Information Extraction Model by Machine Learning to Extract Relation
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 14
%P 30-35
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
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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Index Terms

Computer Science
Information Sciences

Keywords

Arabic Open Information dependency parsing Decision Tree