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SAP: Standard Arabic profiling toolset for textual analysis

  • Khalid M.O. Nahar(corresponding author)
    ,
  • ,
  • Malek Barahoush
    ,
  • Abdallah M. Al-Akhras
*Corresponding author for this work
  • Yarmouk University
Scholary Output:
Contribution to journal
Article
Peer-review

Open access

Abstract

This paper defines a Standard Arabic Profiling (SAP) toolset that helps researchers for textual analysis and comparing between different Arabic corpora. Since tools for Arabic language are needed, we present the SAP toolset to simplify the textual analysis process. The approach consists of three profilers: The Part of Speech (POS) profiler that gives statistical analysis for a given document, vocabulary profiler which provides user with an indication out the vocabulary used in a document with reference to Open Source Arabic Corpus (OSAC) of two news agencies (CNN and BBC). The process is accomplished by computing similarity between documents and corpus using Log likelihood measure. Lastly the newly added profiler is the Readability profiler which is used to 1) assess the readability level for a document according to Flesch Reading Ease Readability Formula, and 2) measure the simplicity and ambiguity levels of the document. We described the current part-of-speech for this toolset and how we can extend its functionality to embrace vocabulary and readability profiling.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 222-229 (8 pages)

Journal (Volume, Issue Number)

International Journal of Machine Learning and Computing (Volume 9, Issue 2)

Publication milestones

  • Published - 04/01/2019

Publication status

Published - 04/01/2019

Publication IDs

  • Scopus: 85064978362

Publication metrics

Metrics

SciVal
FWCI
0.31
SciVal
Author count
4
SciVal
Paper percentile
59
SciVal
citations
2
Scopus
citations
Fractional count
1
Fractional count
0.25
Fractional count
3
Fractional count
0.75
Fractional count
1
Fractional count
1

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Citation count
5
Captures
19

Funding Details

ACKNOWLEDGEMENT We extend our sincere thanks to Yarmouk University - Irbid - Jordan, where this scientific research was supported by the Deanship of Scientific Research and Graduate Studies at the University.