[PDF].pdf

2011-Zolaktaf-NIPS.pdf
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🔗 Source: web.cs.dal.ca
📊 Size: 149 KB
📄 Pages: 5 pages
⬇️ Downloads: 61

Summary

Community Question Answering (CQA) services have large archives of questions and answers, but exploiting this information is a challenge due to redundant questions and lack of semantic information. A statistical topic model is proposed to model Question-Answering archives, capturing relationships between questions and answers by modeling topical dependencies. The model, called Question-Answering Topic Model (QATM), uses two types of latent variables, question topic (Q-topics) and answer topic (A-topics), to distinguish between topics in questions and answers and capture topic dependency and correlation. QATM outperforms the LDA model in retrieving correct answers for query questions and can be used for automatic tagging of questions and answers, enabling topical browsing capabilities for legacy Q&A archives.

Description

Community Question Answering (CQA) services have large archives of questions and answers, but exploiting this information is a challenge due to redundant...

Technical Information

  • File Format: PDF
  • File Size: 149 KB
  • Pages: 5
  • Language: EN
  • Total Downloads: 61
  • Last Updated: 6 days ago

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