Invention Grant
- Patent Title: Probabilistic language models for identifying sequential reading order of discontinuous text segments
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Application No.: US16904881Application Date: 2020-06-18
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Publication No.: US11769111B2Publication Date: 2023-09-26
- Inventor: Trung Huu Bui , Hung Hai Bui , Shawn Alan Gaither , Walter Wei-Tuh Chang , Michael Frank Kraley , Pranjal Daga
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Shook, Hardy & Bacon L.L.P.
- Main IPC: G06F17/00
- IPC: G06F17/00 ; G06Q10/10 ; G06Q10/06 ; G06F40/10 ; G06V30/148 ; G06V30/413 ; G06F40/103

Abstract:
The present invention is directed towards providing automated workflows for the identification of a reading order from text segments extracted from a document. Ordering the text segments is based on trained natural language models. In some embodiments, the workflows are enabled to perform a method for identifying a sequence associated with a portable document. The methods includes iteratively generating a probabilistic language model, receiving the portable document, and selectively extracting features (such as but not limited to text segments) from the document. The method may generate pairs of features (or feature pair from the extracted features). The method may further generate a score for each of the pairs based on the probabilistic language model and determine an order to features based on the scores. The method may provide the extracted features in the determined order.
Public/Granted literature
- US20200320329A1 PROBABILISTIC LANGUAGE MODELS FOR IDENTIFYING SEQUENTIAL READING ORDER OF DISCONTINUOUS TEXT SEGMENTS Public/Granted day:2020-10-08
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