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TZID:Pacific/Honolulu
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CLASS:PUBLIC
CREATED:20261015T135334Z
DESCRIPTION:Topic modeling uses latent dirichlet allocation (LDA) to automatically discover topics contained in a text or group of texts. The topics can then be used for automated classification, or anything else you might imagine in the course of your work. While LDA uses some intensely complex mathematics, it is possible to get a new perspective on the texts you are working with using topic modeling, even if you are not comfortable with the mathematical aspects of the system. The domain knowledge and technical knowledge required to fully understand the topic modeling process can be intimidating, but don't let that stop you from joining us for some experimenting and exploration!\n\n\n\n\nRegistration is required.\n\nhttp://uhmlibrary.libcal.com/event/3561768?&hs=a
DTEND;TZID=Pacific/Honolulu:20171103T020000Z
DTSTAMP:20261015T135334Z
DTSTART;TZID=Pacific/Honolulu:20171103T000000Z
LAST-MODIFIED:20261015T135334Z
LOCATION:Hamilton Library Room 306
PRIORITY:5
SEQUENCE:0
SUMMARY;LANGUAGE=en-us:Text Mining Series – Session 4 - Topic Modeling using MALLET (Hands on)
TRANSP:OPAQUE
UID:179210841431661web-support-l@lists.hawaii.edu
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