An Arabic Grammar Auditor Based on Dependency Grammar

Joint Authors

Alothman, Ameerah
Alsalman, AbdulMalik

Source

Advances in Human-Computer Interaction

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-12-07

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Mathematics

Abstract EN

The Arabic language has many complex grammar rules that may seem complicated to the average user or learner.

Automatic grammar checking systems can improve the quality of the text, reduce the costs of the proofreading process, and play a role in grammar teaching.

This paper presents an initiative toward developing a novel and comprehensive Arabic auditor that can address vowelized texts.

We called the “Arabic Grammar Detector” (AGD-أَجِــدْ).

AGD was successfully implemented based on a dependency grammar and decision tree classifier model.

Its purpose is to extract patterns of grammatical rules from a projective dependency graph in order to designate the appropriate syntax dependencies of a sentence.

The current implementation covers almost all regular Arabic grammar rules for nonvowelized texts as well as partially or fully vowelized texts.

AGD was evaluated using the Tashkeela corpus.

It can detect more than 94% of grammatical errors and hint at their causes and possible corrections.

American Psychological Association (APA)

Alothman, Ameerah& Alsalman, AbdulMalik. 2020. An Arabic Grammar Auditor Based on Dependency Grammar. Advances in Human-Computer Interaction،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1126477

Modern Language Association (MLA)

Alothman, Ameerah& Alsalman, AbdulMalik. An Arabic Grammar Auditor Based on Dependency Grammar. Advances in Human-Computer Interaction No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1126477

American Medical Association (AMA)

Alothman, Ameerah& Alsalman, AbdulMalik. An Arabic Grammar Auditor Based on Dependency Grammar. Advances in Human-Computer Interaction. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1126477

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1126477