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We Wrote the Book on Text Analytics

The KAPS Group is a network of consultants with a wide range of skills and experience in text analytics, taxonomy, ontology and Knowledge graphs, Python and other proprietary text analytics programming languages, and information and knowledge management. KAPS Group was founded by Tom Reamy, author of the most comprehensive book on text analytics, Deep Text.

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What is Text Analytics?

Semantic AI: A Platform for Multiple Applications

Text analytics, often called semantic AI, is a broad umbrella term that includes a large array of capabilities and applications, but the basic definition is that it is the use of software and knowledge models to analyze text and extract key information. The two most important functionalities are auto-categorization and data extraction:

Auto-categorization identifying the main idea(s) of documents, usually using a taxonomy. This is done with machine learning or semantic rules.

Data extraction of entities (people, places, organizations, etc.) and relationships such as companies merging

The Most Comprehensive Book on Text Analytics

The only complete book on text analytics will transform how you get value from all your unstructured text. Deep text is an approach to text analytics that adds depth and intelligence to our ability to utilize a growing mass of unstructured text.

If you want to know more about Deep Text and how the KAPS Group can help you get started using advanced text analytics, please contact us or call (510) 333-2458.

Text Analytics and Semantic AI

Question: How do you make Gen AI smarter, more useful, and more truthful?

Answer: Text Analytics (also known as Semantic AI)

As amazing as ChatGPT and the other Large Language Models are, they have a number of basic limitations:

  • They have a tendency to hallucinate.
  • They are entirely opaque – even their creators don’t know why they say what they do.
  • They were trained on public information which is very different from content behind an enterprise firewall.
  • Public information contains a great deal of bias.

Text analytics, as practiced by the KAPS Group, can help with all four limitations.

  • For help with hallucinations and bias, see Using Text Analytics to fix Fake News .
  • For help with transparency, a semantic AI approach to auto-categorization can open a window into Gen AI’s output.
  • For help with enterprise vocabulary, that is what we have been doing for over 15 years: building text analytics enterprise solutions – see the range of articles and presentations on this site.