Automatic labeling of text data

Number of patents in Portfolio can not be more than 2000

United States of America

PATENT NO 12197486
APP PUB NO 20220414137A1
SERIAL NO

17711506

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Abstract

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The technology described herein determines whether a candidate text is in a requested class by using a generative model that may not be trained on the requested class. The present technology may use of a model trained primarily in an unsupervised mode, without requiring a large number of manual user-input examples of a label class. The may produce a semantically rich positive example of label text from a candidate text and label. Likewise, the technology may produce from the candidate text and the label a semantically rich negative example of label text. The labeling service makes use of a generative model to produce a generative result, which estimates the likelihood that the label properly applies to the candidate text. In another aspect, the technology is directed toward a method for obtaining a semantically rich example that is similar to a candidate text.

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Patent Owner(s)

Patent OwnerAddress
MICROSOFT TECHNOLOGY LICENSING LLCONE MICROSOFT WAY REDMOND WA 98052

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Acharya, Sharada Shirish Seattle, US 6 28
Betser, Michael Abraham Kirkland, US 5 96
Blum, William Bellevue, US 12 44
Chan, Pak On Seattle, US 4 13
Drinic, Milenko Kenmore, US 8 225
Li, Weisheng Bothell, US 32 307
Liu, Sihong Redmond, US 5 35
Poluri, Ravi Kiran Reddy Samammish, US 11 78
Rudnick, Christian Seattle, US 4 20
Sewak, Mohit Pune, IN 27 132

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