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Electronic Edition @ Nist.gov (open Access).pdf

SOIC-RT.pdf
Preview of electronic edition @ nist.gov (open access)
🔗 Source: trec.nist.gov
📊 Size: 261 KB
📄 Pages: 4 pages
⬇️ Downloads: 287

Summary

Social media users receive numerous news notifications, making it difficult to extract relevant information. To address this, a model is needed to filter useful news quickly and accurately. The Text REtrieval Conference (TREC) offers a Real Time Summarization track to explore online user reading preferences on Twitter. The goal is to find the most interesting tweets for users in a timely manner. Two scenarios are considered: push notifications and email digest. A NLP-based model is built to match streaming tweets with user interest profiles and recommend tweets in real-time. The model can be generalized to other social media datasets and applied to other online platforms.

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Description

Social media users receive numerous news notifications, making it difficult to extract relevant information.

Technical Information

  • File Format: PDF
  • File Size: 261 KB
  • Pages: 4
  • Language: EN
  • Total Downloads: 287
  • Last Updated: 1 week ago

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