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

northeastern-crowd.pdf
Preview of electronic edition @ nist.gov (open access)
🔗 Source: trec.nist.gov
📊 Size: 477 KB
📄 Pages: 6 pages
⬇️ Downloads: 167

Summary

Northeastern University participated in the TREC 2013 Crowdsourcing Track, which aimed to evaluate approaches to crowdsourcing high-quality relevance judgments for web pages and search topics. The team used a modified version of the QuickSort algorithm to collect preference judgments, where assessors compared pairs of documents to determine which one was more relevant. This approach was chosen due to its reliability, consistency, and potential to improve the training of learning-to-rank algorithms. The team used a linear search to find the correct position of each document among the sorted pivots, resulting in a reduced number of comparisons (O(n) instead of O(n2)). The experiment used a single assessor and achieved promising results, with the team concluding that their approach showed potential for efficient and accurate crowdsourcing of relevance judgments.

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Northeastern University participated in the TREC 2013 Crowdsourcing Track, which aimed to evaluate approaches to crowdsourcing high-quality relevance judgments...

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  • File Format: PDF
  • File Size: 477 KB
  • Pages: 6
  • Language: EN
  • Total Downloads: 167
  • Last Updated: 1 week ago

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