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Http://ceur-ws.org/V Ol-2266/T1-3.pdf

T1-3.pdf
Preview of http://ceur-ws.org/V ol-2266/T1-3.pdf
🔗 Source: ceur-ws.org
📊 Size: 299 KB
📄 Pages: 3 pages
⬇️ Downloads: 25

Summary

DAIICT-Hildesheim participated in the IRMiDis 2018 track with three runs to distinguish between fact-checkable and non-fact-checkable tweets. Run 1 and 2 used semantic analysis and word embedding, while Run 3 used a weakly supervised approach with convolutional neural networks. The results showed that Run 3 achieved the best performance, with a precision of 0.4000, recall of 0.2002, and MAP of 0.1471.

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DAIICT-Hildesheim participated in the IRMiDis 2018 track with three runs to distinguish between fact-checkable and non-fact-checkable tweets.

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  • File Format: PDF
  • File Size: 299 KB
  • Pages: 3
  • Language: EN
  • Total Downloads: 25
  • Last Updated: 2 months ago

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