Let’s look at three popular open source NLP tools that developers and data scientists are using to perform discovery on unstructured documents and develop production-ready NLP processing engines.

Big data analytics in healthcare has largely been about looking at claims, electronic health records (EHR) and other forms of structured data. Natural language processing (NLP) is an emerging area ...

In recent years, NLP has undergone significant changes that have made it increasingly easier for users at all skill levels to handle and explore data without being a data scientist. The adoption of ...

The degree to which some languages are underrepresented in data sets is well-recognized, but the ways in which the effect is magnified throughout the NLP toolchain is less discussed, the ...

NLP is adept at mining a wide variety of content types and tying them together with common metadata elements such as: • Named entities: People, companies, places, emails, phone numbers, etc.

Clinical-grade medical NLP software reads and understands unstructured clinical notes—capabilities lacking in traditional NLP. It can extract data from these free-text notes in a structured ...

Sinequa enhances NLP and data connectors. Sinequa, a provider of enterprise search solutions, has added new capabilities in its platform. With an expansion of its natural language processing (NLP) ...

NLP has made it possible to identify content, such as the security size, side of the market and intent related to an inquiry, within chat room text that can be digitized for use within users ...