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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20210402T160031Z
LOCATION:Track 8
DTSTART;TZID=America/New_York:20201118T162400
DTEND;TZID=America/New_York:20201118T163500
UID:submissions.supercomputing.org_SC20_sess355_spostu110@linklings.com
SUMMARY:Diving for Treasure in a Sea of Scientific Literature: Extracting 
 Scientific Information from Free Text Articles
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster\n\nDiving for Treasure in a Se
 a of Scientific Literature: Extracting Scientific Information from Free Te
 xt Articles\n\nKoripelly\n\nIt has become impossible for researchers to ke
 ep up with the more than 2.5 million publications published every year. We
  explore scalable approaches for automatically extracting relations from s
 cientific papers (e.g., melting point of a polymer). We implement a depend
 ency parser-based relation extraction model to understand relationships wi
 thout the need for a Named Entity tagger, and integrate several word embed
 dings models and custom tokenization to boost learning performance for sci
 entific text. We then evaluated the models based on run-time, hyperparamet
 er tuning, and scalability.\n\nTag: Student Program\n\nRegistration Catego
 ry: Tech Program Reg Pass
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