公开(公告)号：US10133813B2

公开(公告)日：2018-11-20

申请号：US14824939

申请日：2015-08-12

申请人： ADOBE SYSTEMS INCORPORATED

发明人： Shawn Alan Gaither ,  Eylon Stroh ,  Priyank Mathur ,  Randy Swineford

IPC分类号： G06F17/30 ,  G06F17/27

摘要： Embodiments of the present invention provide systems, methods, and computer storage media directed at predicting values for an electronic form. In embodiments, the method can include forming synonym groupings of form field labels for a number of users. The synonym groupings can be based on an analysis of the similarity of form field values that are associated with form field labels. In embodiments a predictive model may be generated from these synonym groupings. The predictive model can correlate the synonym groupings of one user with synonym groupings of one or more additional users to enable a determination of one or more predicted form field values for the one user based on a queried form field label even though the one user may have never submitted an electronic form with the queried form field label. Other embodiments may be described and/or claimed.

公开(公告)号：US20180373952A1

公开(公告)日：2018-12-27

申请号：US15630779

申请日：2017-06-22

申请人： ADOBE SYSTEMS INCORPORATED

发明人： Trung Huu Bui ,  Hung Hai Bui ,  Shawn Alan Gaither ,  Walter Wei-Tuh Chang ,  Michael Frank Kraley ,  Pranjal Daga

IPC分类号： G06K9/34 ,  G06F17/21 ,  G06K9/00 ,  G06K9/72 ,  G06Q10/10 ,  G06Q10/06

摘要： 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.