Tasaheel: An Arabic Automative Textual Analysis Tool-All in One

This paper demonstrates Tasaheel, an automative Arabic textual analysis tool. It offers two types of textual analysis utilities: traditional natural language processing tasks; such as stemming, segmentation, normalization, name entity recognition, and part of speech tagging, by integrating open-sour...

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Bibliographic Details
Published in:IEEE access 2023, Vol.11, p.139979-139992
Main Authors: Himdi, Hanen T., Assiri, Fatmah Y.
Format: Article
Language:English
Subjects:
Affixes
Arabic language
Corpus analysis
Data search
development
Linguistics
Morphology
Natural language processing
NLP
Polarity
Segmentation
Speech
Speech recognition
Tagging
Tagging (Computational linguistics)
Task analysis
Text analysis
Words (language)
Writing
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Summary:This paper demonstrates Tasaheel, an automative Arabic textual analysis tool. It offers two types of textual analysis utilities: traditional natural language processing tasks; such as stemming, segmentation, normalization, name entity recognition, and part of speech tagging, by integrating open-sourced Arabic natural language processing packages. The second type of utility offers novel corpus analysis methods, including a detailed word use summary of part of speech, emotion, polarity, linguistics, and domain-specific word labeling. Tasaheel is the first Arabic tool that analyses affixes as a type of comprehensive textual analysis, along with options to search and handle data. We anticipate that Tasaheel will be a conducive tool for Arabic textual analysis.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3340520