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UID:20241105T220000-4553-www.cs.iastate.edu
DTSTART:20241105T220000Z
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TRANSP:OPAQUE
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SUMMARY:Ph.D. Final Oral Exam: Kang Zhou
CLASS:PUBLIC
DESCRIPTION:Speaker:Kang ZhouInformation Extraction with Weak Supervision\n
 \nIn this research\, we introduce novel weak supervision techniques to add
 ress key challenges in information extraction\, specifically in Named Enti
 ty Recognition (NER)\, Relation Extraction (RE)\, and Entity Linking (EL).
  Traditional methods in these areas rely heavily on manual annotations\, w
 hich are expensive and time-consuming. To overcome this\, we propose three
  innovative approaches that significantly reduce the need for human labeli
 ng while maintaining strong performance.\n\nMore information at: https://w
 ww.cs.iastate.edu/event/2024/phd-final-oral-exam-kang-zhou
DTSTAMP:20260713T095011Z
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