Unsupervised Learning Of Rhetorical Structure With Un-topic Models.pdf

C14-1002.pdf
Preview of Unsupervised learning of rhetorical structure with un-topic models
🔗 Source: aclanthology.org
📊 Size: 211 KB
👤 Author: Diarmuid O Seaghdha ; Simone Teufel
⬇️ Downloads: 117

Summary

Researchers propose a Bayesian latent-variable model, BOILERPLATE-LDA, to induce conventional aspects of rhetorical language in scientific writing. The model is based on the hypothesis that rhetorical language is general and independent of the document's topic. It assigns responsibility for generating each word in an abstract to a document-specific topic model or to a rhetorical language model. The model is evaluated in two settings: unsupervised argumentative zoning and providing features for a supervised AZ classifier, showing promising results.

Description

Researchers propose a Bayesian latent-variable model, BOILERPLATE-LDA, to induce conventional aspects of rhetorical language in scientific writing.

Technical Information

  • File Format: PDF
  • File Size: 211 KB
  • Pages: 12
  • Language: EN
  • Author: Diarmuid O Seaghdha ; Simone Teufel
  • Total Downloads: 117
  • Last Updated: 5 hours ago

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