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Systems and methods for document classification are described. Embodiments of the present disclosure generate classification data for a plurality of samples using a neural network trained to identify a plurality of known classes; select a set of samples for annotation from the plurality of samples u...

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Bibliographic Details
Main Authors Greene, Andrew Marc, Gu, Jiuxiang, Lipka, Nedim, Yuan, Michelle, Bangalore Naresh, Smitha, Barmpalios, Nikolaos, Deshpande, Ruchi, Morariu, Vlad Ion, Nenkova, Ani Nenkova, Jain, Rajiv Bhawanji, Zhang, Ruiyi, Manjunatha, Varun
Format Patent
LanguageEnglish
Published 25.04.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:Systems and methods for document classification are described. Embodiments of the present disclosure generate classification data for a plurality of samples using a neural network trained to identify a plurality of known classes; select a set of samples for annotation from the plurality of samples using an open-set metric based on the classification data, wherein the annotation includes an unknown class; and train the neural network to identify the unknown class based on the annotation of the set of samples.
Bibliography:Application Number: US202218048900