MetRec: A dataset for meter classification of arabic poetry

In this data article, we report a dataset related to the research titled “Meter Classification of Arabic Poems Using Deep Bidirectional Recurrent Neural Networks”[2]. The dataset was collected from a large repository of Arabic poems, Aldiwan website [1]. The data collection was done using a Python s...

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Detalles Bibliográficos
Autores principales: Al-shaibani, Maged S., Alyafeai, Zaid, Ahmad, Irfan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653274/
https://www.ncbi.nlm.nih.gov/pubmed/33204783
http://dx.doi.org/10.1016/j.dib.2020.106497
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author Al-shaibani, Maged S.
Alyafeai, Zaid
Ahmad, Irfan
author_facet Al-shaibani, Maged S.
Alyafeai, Zaid
Ahmad, Irfan
author_sort Al-shaibani, Maged S.
collection PubMed
description In this data article, we report a dataset related to the research titled “Meter Classification of Arabic Poems Using Deep Bidirectional Recurrent Neural Networks”[2]. The dataset was collected from a large repository of Arabic poems, Aldiwan website [1]. The data collection was done using a Python script that scrapes the website to find the poems and their associated meters. The dataset contains the verses and their corresponding meter classes. Meter classes are represented as numbers from 0 to 13. The dataset can be highly useful for further research in order to improve the field of Arabic poems’ meter classification.
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spelling pubmed-76532742020-11-16 MetRec: A dataset for meter classification of arabic poetry Al-shaibani, Maged S. Alyafeai, Zaid Ahmad, Irfan Data Brief Data Article In this data article, we report a dataset related to the research titled “Meter Classification of Arabic Poems Using Deep Bidirectional Recurrent Neural Networks”[2]. The dataset was collected from a large repository of Arabic poems, Aldiwan website [1]. The data collection was done using a Python script that scrapes the website to find the poems and their associated meters. The dataset contains the verses and their corresponding meter classes. Meter classes are represented as numbers from 0 to 13. The dataset can be highly useful for further research in order to improve the field of Arabic poems’ meter classification. Elsevier 2020-11-04 /pmc/articles/PMC7653274/ /pubmed/33204783 http://dx.doi.org/10.1016/j.dib.2020.106497 Text en © 2020 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Al-shaibani, Maged S.
Alyafeai, Zaid
Ahmad, Irfan
MetRec: A dataset for meter classification of arabic poetry
title MetRec: A dataset for meter classification of arabic poetry
title_full MetRec: A dataset for meter classification of arabic poetry
title_fullStr MetRec: A dataset for meter classification of arabic poetry
title_full_unstemmed MetRec: A dataset for meter classification of arabic poetry
title_short MetRec: A dataset for meter classification of arabic poetry
title_sort metrec: a dataset for meter classification of arabic poetry
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653274/
https://www.ncbi.nlm.nih.gov/pubmed/33204783
http://dx.doi.org/10.1016/j.dib.2020.106497
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