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Number Parser.pdf

ki2017.pdf
Preview of Number Parser
🔗 Source: heikopaulheim.com
📊 Size: 707 KB
📄 Pages: 7 pages
⬇️ Downloads: 361

Summary

A robust number parser based on Conditional Random Fields is proposed to parse numbers from unstructured sources, achieving an accuracy of over 90%. The parser uses pairs of Wikipedia infobox entries and numbers from public knowledge graphs as training data, and can handle different number formats and separators. The approach involves tagging raw strings, training a CRF model, and applying the model to parse numbers from new strings. Evaluation on a sample of HTML tables shows that the approach outperforms two baseline methods, including the built-in Java floating-point parser and the Mannheim Search Join Engine's number parsing engine.

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Description

A robust number parser based on Conditional Random Fields is proposed to parse numbers from unstructured sources, achieving an accuracy of over 90%.

Technical Information

  • File Format: PDF
  • File Size: 707 KB
  • Pages: 7
  • Language: EN
  • Total Downloads: 361
  • Last Updated: 3 weeks ago

Document Overview

This PDF document about Number Parser provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Number Parser.

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