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🔗 Source: linguistics.rub.de
📊 Size: 396 KB
📄 Pages: 6 pages
⬇️ Downloads: 139

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Syntax-based semantic spaces are more flexible and can better model semantic relatedness than bag-of-words spaces, but their application is limited by sparsity and restricted coverage. Smoothing syntax-based spaces with word-based spaces can improve coverage while maintaining prediction quality. The best results are obtained by picking the maximal predicted similarity for each word pair, taking advantage of the tendency of unreliable models to underestimate similarity. Experiments on two German benchmark tasks show that this approach can combine the high precision of syntax-based spaces with the high coverage of bag-of-words spaces.

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Syntax-based semantic spaces are more flexible and can better model semantic relatedness than bag-of-words spaces, but their application is limited by sparsity...

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  • File Format: PDF
  • File Size: 396 KB
  • Pages: 6
  • Language: EN
  • Total Downloads: 139
  • Last Updated: 1 week ago

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