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DTSTART:20050403T070000
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DTSTART:20051030T060000
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UID:69ba1ef39b724
DTSTART;TZID=America/Toronto:20060127T113000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20060127T113000
URL:https://uwaterloo.ca/artificial-intelligence-group/events/ai-seminar-se
 gment-based-hidden-markov-models-information
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2306C (AI lab) Waterloo ON N2L 3G1 Canada
SUMMARY:AI seminar: Segment-based hidden Markov models for information\next
 raction
CLASS:PUBLIC
DESCRIPTION:Speaker: Zhenmei Gu\n\nHidden Markov models (HMMs) are powerful
  statistical models that have\nfound successful applications in Informatio
 n Extraction (IE). In\ncurrent approaches to applying HMMs to IE\, an HMM 
 is used to model\ntext at the document level\, i.e.\, the entire document 
 is modeled by an\nHMM. This modeling might cause undesired redundancy in e
 xtraction in\nthe sense that more than one filler is identified and extrac
 ted.
DTSTAMP:20260318T034139Z
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