Beyond String Matching: Semantic Evaluation of PDF Table Extraction

1. 1Generate synthetic PDFs with precise LaTeX ground truth using tables from arXiv
2. 2Develop a benchmarking framework to evaluate table extraction tools
3. 3Apply semantic metrics to assess the equivalence of extracted table content
4. 4Configure the framework to handle diverse and complex tables
5. 5Test the framework using various table extraction tools and algorithms
6. 6Analyze the results to identify areas for improvement in table extraction

Data scientists and researchers on a team benefit from this approach as it enables more accurate extraction of tables from PDFs, while software engineers can utilize this framework to develop more robust table extraction tools

💡 Semantic metrics can capture more nuanced aspects of table content than traditional string matching approaches

📊 Improve PDF table extraction with semantic evaluation metrics 📈