Cognitive document image digitization

    公开(公告)号:GB2582722B

    公开(公告)日:2021-03-03

    申请号:GB202009558

    申请日:2018-11-23

    Applicant: IBM

    Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a document image with objects and identifying microblocks corresponding to each object. Analyzing a position of a microblock for collinearity with another microblock based on respective positional characteristics and adjustable collinearity parameters. Collinear microblocks are identified into a macroblock and computational data of a key-value pair is created from the macroblock. A heuristic confidence level is associated with the key-value pair. Also based on data cluster formation, a table may be classified and data extracted.

    Blockwise extraction of document metadata

    公开(公告)号:GB2583290A

    公开(公告)日:2020-10-21

    申请号:GB202009894

    申请日:2018-11-23

    Applicant: IBM

    Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a document image, wherein the document image includes a plurality of objects; identifying a plurality of macroblocks within the document image; performing microblock processing within macroblocks of the plurality of macroblocks, wherein the microblock processing includes examining content of microblocks within a macroblock for extraction of key-value pairs, the examining content including performing an ontological analysis of microblocks, wherein the microblock processing includes associating confidence levels to the extracted key-value pairs; and outputting metadata based on the performing microblock processing within macroblocks of the plurality of macroblocks.

    Blockwise extraction of document metadata

    公开(公告)号:GB2583290B

    公开(公告)日:2022-03-16

    申请号:GB202009894

    申请日:2018-11-23

    Applicant: IBM

    Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a document image, wherein the document image includes a plurality of objects; identifying a plurality of macroblocks within the document image; performing microblock processing within macroblocks of the plurality of macroblocks, wherein the microblock processing includes examining content of microblocks within a macroblock for extraction of key-value pairs, the examining content including performing an ontological analysis of microblocks, wherein the microblock processing includes associating confidence levels to the extracted key-value pairs; and outputting metadata based on the performing microblock processing within macroblocks of the plurality of macroblocks.

    Cognitive document image digitization

    公开(公告)号:GB2582722A

    公开(公告)日:2020-09-30

    申请号:GB202009558

    申请日:2018-11-23

    Applicant: IBM

    Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a document image with objects and identifying microblocks corresponding to each object. Analyzing a position of a microblock for collinearity with another microblock based on respective positional characteristics and adjustable collinearity parameters. Collinear microblocks are identified into a macroblock and computational data of a key- value pair is created from the macroblock. A heuristic confidence level is associated with the key-value pair. Also based on data cluster formation, a table may be classified and data extracted.

    Semantic normalization in document digitization

    公开(公告)号:GB2581461A

    公开(公告)日:2020-08-19

    申请号:GB202009248

    申请日:2018-11-30

    Applicant: IBM

    Abstract: A method for normalizing a key in a document image includes identifying a candidate key corresponding to an object in a document image with a key in key ontology data, based on that the candidate key is semantically interchangeable with the key. A context, position, and style of each objects of the document image is represented in the document metadata. The candidate key is normalized into a normal form. A key class corresponding to the normal form is determined and a confidence score indicating a likelihood of the key class being representative of the candidate key is assessed. A semantic database is updated with the key class upon verification for enhanced processing of future documents.

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