BrajText-Saar: A structured cultural dataset for cultural text mining in indian heritage texts

IF 1.9 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-07-16 DOI:10.1016/j.dib.2026.113086

Mukta M. Deshpande, Prafulla B. Bafna

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引用次数: 0

Abstract

India is one of the countries where many regional languages are spoken in different parts of the country. Each part of the country has its unique cultural traditions; therefore, an abundance of cultural texts is available in Indian Regional languages. The cultural texts are mostly ancient scriptures that represent the community's heritage, values, and ancient knowledge. Braj is one of the Indian regional languages that represents the cultural heritage of the Braj region. The BrajText-Saar dataset contains texts from the Braj language, which features a variety of prehistoric scripts. The data was collected from the Maan Mandir trust's portal, which operates to maintain Braj culture and heritage. The Braj text primarily explains the divine actions and the life of Lord Krishna in the form of poetry and devotional songs. Offline Braj literature from renowned writers is available in manuscript form. This represents an opportunity for cultural text mining in the Braj Language. The developed dataset opens new paths in various research areas, including language studies, sentiment analysis, and emotion analysis, and is also suitable for digital humanities research.

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BrajText-Saar：一个结构化的文化数据集，用于印度传统文本的文化文本挖掘

印度是一个在不同地区使用许多地方语言的国家之一。这个国家的每个地区都有其独特的文化传统；因此，印度地区语言中有丰富的文化文本。文化文本大多是古老的经文，代表了社区的遗产、价值观和古老的知识。布拉吉语是印度地区语言之一，代表着布拉吉地区的文化遗产。BrajText-Saar数据集包含来自Braj语言的文本，该语言以各种史前文字为特色。这些数据是从Maan Mandir信托基金的门户网站收集的，该网站致力于维护巴西文化和遗产。布拉吉文主要以诗歌和祈祷歌曲的形式解释神的行为和主奎师那的生活。来自知名作家的布拉吉文学作品以手稿形式提供。这为在巴西语中进行文化文本挖掘提供了机会。开发的数据集在语言研究、情感分析、情感分析等多个研究领域开辟了新的路径，也适用于数字人文研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.