Hybrid Machine Learning

dataset link : https://www.kaggle.com/datasets/osamahosamabdellatif/high-quality-invoice-images-for-ocr Overview High-Quality Invoice Images for OCR is a curated dataset containing professionally scanned and digitally captured invoice documents. It is designed for training, fine-tuning, and evaluating OCR models, machine learning pipelines, and data extraction systems. This dataset focuses on clean, structured invoices to simulate real-world scenarios in financial document automation. What's Inside 📄 Variety of invoice templates from multiple industries (e.g., retail, manufacturing, services) 🖋️ Different currencies, tax formats, and layouts 📸 High-resolution scanned and photographed invoices 🏷️ Optional field annotations (e.g., invoice number, date, total amount, vendor name) for supervised training Key Applications Training and fine-tuning OCR and Document AI models Machine learning for structured and semi-structured data extraction Intelligent Document Processing (IDP) and Robotic Process Automation (RPA) Benchmarking table detection, key-value extraction, and layout analysis models Why Use This Dataset? ✅ High-quality images optimized for OCR and data extraction tasks ✅ Real-world invoice variations to improve model robustness ✅ Ideal for machine learning workflows in finance, ERP, and accounting systems ✅ Supports rapid prototyping for invoice understanding models Ideal For Researchers working on OCR and document understanding Developers building invoice processing systems Machine learning engineers fine-tuning models for data extraction Startups and enterprises automating financial workflows

The Guided Lexrank algorithm is applied to dataset special_appeal.csv to summarize the texts of legal documents. The obtained summary and the texts of the topics contained in dataset themes.csv are submitted to the BM25 algorithm for similarity assessment. From a list of topics, the GLARE method produces a ranking with suggested topics for a given document.