Privacy preserving document analysis

Number of patents in Portfolio can not be more than 2000

United States of America

PATENT NO 12267305
APP PUB NO 20230336532A1
SERIAL NO

18317338

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Abstract

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Systems and techniques for privacy preserving document analysis are described that derive insights pertaining to a digital document without communication of the content of the digital document. To do so, the privacy preserving document analysis techniques described herein capture visual or contextual features of the digital document and creates a stamp representation that represents these features without included the content of the digital document. The stamp representation is projected into a stamp embedding space based on a stamp encoding model generated through machine learning techniques capturing feature patterns and interaction in the stamp representations. The stamp encoding model exploits these feature interactions to define similarity of source documents based on location within the stamp embedding space. Accordingly, the techniques described herein can determine a similarity of documents without having access to the documents themselves.

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Patent Owner(s)

Patent OwnerAddress
ADOBE INCSAN JOSE CA

International Classification(s)

Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Barmpalios, Nikolaos Sunnyvale, US 14 40
Deshpande, Ruchi Rajiv Belmont, US 2 3
Gaither, Shawn Alan Raleigh, US 10 60
Greene, Andrew Marc Newton, US 5 47
Kraley, Michael Lexington, US 11 97
Rezvani, Nargol Sunnyvale, US 2 3
Swineford, Randy Lee Sunnyvale, US 7 75

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