BackGenerative AI Datasets
Large-Scale Professional Domain Corpus Dataset - Chinese
Introducing our state-of-the-art Generative AI Dataset Product, tailored for large-scale professional domain Chinese corpus datasets. maadaa.ai has developed the comprehensive automated parsing and data structuring engine which can seamlessly support most of the popular e-book formats including PDF, EPUB, mobi, azw(3), and DjVu. Leveraging this engine, we can accurately restore formulas within PDF documents to Latex text, ensuring complex equations and multiline formulas are recognized with precision.The Markdown format plays a pivotal role in highlighting the capabilities of multi-modal data, especially in the context of promoting the extensive dataset we previously discussed. This dataset, designed for the training of multi-modal large models, benefits significantly from Markdown's ability to seamlessly integrate text with multimedia content. Furthermore, our engine meticulously reproduces the original layout of PDF documents, ensuring text paragraphs, headings, subscripts, and superscripts are cleanly separated, and formulas and diagrams remain unscrambled.
Product Overview
Product Name:
Large-Scale Professional Domain Corpus Dataset - Chinese
Data Type:
Multi-modal corpus, markdown format, with embedded images
Data Collection Method:
licensed or license-free e-books
Key Features:
  • 120M Electronic Documents
  • 2PB fine structured data
  • Most of popular e-book formats
  • Hundred of professional domains
  • Comprehensive Format Support:most of the popular e-book formats such as PDF, EPUB, mobi, azw(3), and DjVu.
  • Advanced OCR engine for Formulas:Equations and multiline formulas in PDFs are transformed into Latex text with high accuracy.
  • Precise Layout Reproduction:Ensures the original formatting of PDFs is preserved, including text arrangement, headings, and diagrams.
Application Scenarios:
Generative AI enabled search engine, chatbot, professional Q&A,professional assistants, domain-specific content generation, etc.

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