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[[File:Table-extraction-simple-table.png|thumb|300px|Data in an Excel spreadsheet is an example of tabular data.]] | [[File:Table-extraction-simple-table.png|thumb|300px|Data in an Excel spreadsheet is an example of tabular data.]] | ||
<blockquote style="font-size:14pt"> | <blockquote style="font-size:14pt"> | ||
[[ | ''[[Row Match]]'' | ||
</blockquote> | </blockquote> | ||
''Row Match'' is one of three [[Table Extraction]] methods available to '''Data Table''' '''Data Elements''' to extract information from tables on a document set. It uses regular expression pattern matching to determine a tables structure based on the pattern of each row and extract cell data from each column. | |||
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The earliest examples of OCR (Optical Character Recognition) can be traced back to the 1870s. Early OCR devices were actually invented to aid the blind. This included "text-to-speech" devices that would scan black print and produce sounds a blind person could interpret, as well as "text-to-tactile" machines which would convert luminous sensations into tactile sensations. Machines such as these would allow a blind person to read printed text not yet converted to Braille. | The earliest examples of OCR (Optical Character Recognition) can be traced back to the 1870s. Early OCR devices were actually invented to aid the blind. This included "text-to-speech" devices that would scan black print and produce sounds a blind person could interpret, as well as "text-to-tactile" machines which would convert luminous sensations into tactile sensations. Machines such as these would allow a blind person to read printed text not yet converted to Braille. |
Revision as of 16:12, 2 March 2021
Getting Started | |||
Grooper was built from the ground up by BIS, a company with 35 years of continuous experience developing and delivering new technology. Grooper is an intelligent document processing and digital data integration solution that empowers organizations to extract meaningful information from paper/electronic documents and other forms of unstructured data. The platform combines patented and sophisticated image processing, capture technology, machine learning, natural language processing, and optical character recognition to enrich and embed human comprehension into data. By tackling tough challenges that other systems cannot resolve, Grooper has become the foundation for many industry-first solutions in healthcare, financial services, oil and gas, education, and government. |
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Row Match is one of three Table Extraction methods available to Data Table Data Elements to extract information from tables on a document set. It uses regular expression pattern matching to determine a tables structure based on the pattern of each row and extract cell data from each column. |
The earliest examples of OCR (Optical Character Recognition) can be traced back to the 1870s. Early OCR devices were actually invented to aid the blind. This included "text-to-speech" devices that would scan black print and produce sounds a blind person could interpret, as well as "text-to-tactile" machines which would convert luminous sensations into tactile sensations. Machines such as these would allow a blind person to read printed text not yet converted to Braille. The first business to install an OCR reader was the magazine Reader's Digest in 1954. The company used it to convert typewritten sales reports into machine readable punch cards. It would not be until 1974 that OCR starts to form as we imagine it now with Ray Kurzweil's development of the first "omni-font" OCR software, capable of reading text of virtually any font. |
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