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US Patent 10049270 Using visual features to identify document sections

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Contents

Is a
Patent
Patent

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10049270
Patent Inventor Names
Rizwan Dudekula0
Sujoy Sett0
Lalit Agarwalla0
Purushothaman K. Narayanan0
Date of Patent
August 14, 2018
Patent Application Number
15857682
Date Filed
December 29, 2017
Patent Citations Received
‌
US Patent 12135939 Systems and methods for deviation detection, information extraction and obligation deviation detection
0
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US Patent 11256856 Method, device, and system, for identifying data elements in data structures
0
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US Patent 11636147 Training neural networks to perform tag-based font recognition utilizing font classification
0
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US Patent 11321956 Sectionizing documents based on visual and language models
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US Patent 11763079 Systems and methods for structure and header extraction
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US Patent 11803706 Systems and methods for structure and header extraction
‌
US Patent 11886814 Systems and methods for deviation detection, information extraction and obligation deviation detection
0
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US Patent 11475209 Device, system, and method for extracting named entities from sectioned documents
...
Patent Primary Examiner
‌
Aklilu Woldemariam
Patent abstract

A method, computer system, and a computer program product for identifying sections in a document based on a plurality of visual features is provided. The present invention may include receiving a plurality of documents. The present invention may also include extracting a plurality of content blocks. The present invention may further include determining the plurality of visual features. The present invention may then include grouping the extracted plurality of content blocks into a plurality of categories. The present invention may also include generating a plurality of closeness scores for the plurality of categories by utilizing a Visual Similarity Measure. The present invention may further include generating a plurality of Association Matrices on the plurality of categories for each of the received plurality of documents based on the Visual Similarity Measure. The present invention may further include merging the plurality of categories into a plurality of clusters.

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