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
Descripción
Sumario: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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