Short note on Information Extraction

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 Information Extraction 

 Information extraction is the process of extracting information from unstructured textual sources to enable finding entities as well as classifying and storing them in a database. Semantically enhanced information extraction (also known as semantic annotation) couples those entities with their semantic descriptions and connections from a knowledge graph. By adding metadata to the extracted concepts, this technology solves many challenges in enterprise content management and knowledge discovery.

Typical Information Extraction Applications

Information extraction can be applied to a wide range of textual sources: from emails and Web pages to reports, presentations, legal documents, and scientific papers. The technology successfully solves challenges related to content management and knowledge discovery in the areas of:

  • Business intelligence (for enabling analysts to gather structured information from multiple sources);
  • .Financial investigation (for analysis and discovery of hidden relationships); 
  • Scientific research (for automated references discovery or relevant papers suggestion);
  • Media monitoring (for mentions of companies, brands, people);
  • Healthcare records management (for structuring and summarizing patients' records); 
  • Pharma research (for drug discovery, adverse effects discovery and clinical trials automated analysis).

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