Fmr Corp.

Punitha Chandrasekar

Bidhan Roy

Vinay Iyengar

Ankit Kumar Garg

Hui Su

Amol Vinayak Jadhav

Rachna Saxena

Shyam Subramanian

Mohamed Mahdi Alouane

Ananya Bal

Sourav Karmakar

Keerthan Ramnath

Victor S Y Lo

Varun Vivek Aher

Systems and methods for extracting data from electronic documents using optical character recognition (OCR) and non-OCR based text extraction. A server computing device initiates non-OCR based text extraction for each page of an electronic document. The server calculates a document text coverage percentage corresponding to the non-OCR based text extraction for the whole document and, in response to determining that the document text coverage percentage is below a first threshold, initiates OCR for the document. The server calculates a page text coverage percentage corresponding to the non-OCR based text extraction for one or more pages of the electronic document and, in response to determining that the page text coverage percentage is below a second threshold, initiates OCR for the pages. The server combines first text extracted from the electronic document using non-OCR based text extraction and second text extracted from the electronic document using OCR.

Systems and methods for automated end-to-end text extraction of electronic documents

Methods and apparatuses are described for automatically identifying text sections of a document to generate a searchable hierarchical data structure. A computing device receives a document comprising text entities and converts the document from a first format to a second format, including generating metadata associated with text alignment, text position, text spacing, or fonts. The computing device extracts the text blocks, including determining coordinates associated with each text block using the metadata. The computing device determines document sections using the document metadata by identifying strings in the extracted text blocks that indicate a presence of a bullet point in the document, assigns a hierarchical category to each identified document section, and inserts text of each document section into a hierarchical data structure based upon the assigned hierarchical category. The computing device traverses the hierarchical data structure using search request data to identify document sections relating to the search request data.

Automatic identification of document sections to generate a searchable data structure

Systems and methods for extracting data from electronic documents based on data patterns. The method includes receiving electronic template documents. Each template document corresponds to a type of electronic document. The method further includes, for each template document, processing the template document using a text extraction and data processing application. The method also includes, for each template document, determining a data extraction formula corresponding to the type of electronic document. The method further includes, storing the data extraction formula in a first database. The method also includes, receiving an electronic document including user data and a Unicode corresponding to the type of document. The method also includes, processing and classifying the electronic document into the type of document corresponding to the Unicode. The method also includes identifying data elements in the electronic document based on the data extraction formula and extracting data values for each of the identified data elements.

Systems and methods for data extraction from electronic documents using data patterns

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Bengaluru, India

Punitha Chandrasekar