Finch Computing Releases First Whitepaper on its Text Analysis Solution, Finch for Text

Reston, VA – Finch Computing, a division of Qbase, LLC, today released its first product whitepaper since the company’s rebranding and product consolidation last month. The newly published Finch for Text whitepaper is the first in a series of whitepapers on Finch Computing’s innovative data analytics technologies.

“We hear from customers and potential customers that analyzing the volumes of unstructured content they possess – research reports, news articles, Word documents, emails – is something they’ve never been able to do effectively,” Finch Computing’s EVP of Communications and Marketing Caryn Alagno said. “Finch for Text does just that. It reads those documents like a human would and gives them actionable, quantifiable insights about the content within them– and, ultimately, their value. From there, they can make better, more informed decisions.”

Finch for Text is an entity extraction and disambiguation service that employs natural language processing, sophisticated statistical models and other heuristics to isolate and extract eight distinct entity types from unstructured text: people, places, organizations, cyber entities, IP addresses, phone numbers, currency values and dates and times. It then correctly disambiguates between same-named or similarly named entities by taking in all the relevant context surrounding these entities.

Finch for Text was developed based on Qbase’s experience understanding geographic references within unstructured text in the intelligence community with our former MetaCarta product.

“We’re excited about what’s ahead for Finch for Text,” Alagno continued. “It builds on a trusted, proven product to offer support for more entity types and with greater accuracy. In an environment where text analysis is needed more than ever, Finch for Text can serve as the foundation for an enterprise-wide unstructured text strategy.”


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