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Using Word Semantics On Entity Names For Correspondence Set Generation.pdf

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Preview of Using word semantics on entity names for correspondence set generation
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📊 Size: 125 KB
📄 Pages: 2 pages
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Summary

Rafael Vieira and Kate Revoredo propose using word semantics on entity names for correspondence set generation in ontology matching, exploiting word-word similarities in the GloVe model. They built a prototype that associates each entity with a vector based on its name and calculates cosine similarity to generate correspondences. The prototype was evaluated against baselines from OAEI, showing promising results, with precision and F1-measure comparable to the baselines, but low recall due to errors on tests with random entity names and out-of-vocabulary words.

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Rafael Vieira and Kate Revoredo propose using word semantics on entity names for correspondence set generation in ontology matching, exploiting word-word...

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  • File Format: PDF
  • File Size: 125 KB
  • Pages: 2
  • Language: EN
  • Total Downloads: 109
  • Last Updated: 6 days ago

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This PDF document about Using word semantics on entity names for correspondence set generation provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Using word semantics on entity names for correspondence set generation.

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