What is text analysis (TA)?
Text analysis is the automated processing of unstructured or "free text" to extract critical information. Accurate text analysis requires the integration of a broad range of approaches,
collectively called natural language processing (NLP).
For example, extracting business information from a Wall Street Journal article to determine which company had which earnings during which time periods is a very tricky undertaking that keyword, statistical, and
neural network systems cannot begin to tackle. This is the type of information a text analysis system can determine accurately and reliably.
Partially formatted text (e.g., newswire) and fully formatted texts (e.g., HTML) can also be processed by the same methods. The hard job is the unstructured text within the formatting.
Why the focus on text analysis?
Most of what people do with computers centers on text.
People create, transfer, read, search, edit, and otherwise transform textual information in myriad ways. Yet automated understanding of the content of text remains an elusive goal for today's technology, despite the huge potential and need for such technology.
TextAI's mission is no less than to revolutionize the state of the art and to bring comprehensive text analysis tools to the marketplace.
How is TAI's text analysis technology unique?
VisualText® is the first integrated development environment (IDE) for natural language processing. It integrates multiple strategies, including statistical, keyword, grammar-based, and pattern-based, as well as diverse information sources, including linguistic, conceptual, and domain knowledge, to quickly and efficiently develop text analysis applications.
The NLP++® programming language and Conceptual Grammar knowledge base management system combine with the GUI tools within VisualText to provide a self-contained and fast edit-and-test development environment.
VisualText enables users to conveniently maintain and enhance their text analysis applications with reduced need for linguistic and programming expertise, and with reduced reliance on TextAI for
maintenance and support. This is made possible by our patent-pending methods for automatically generating rules from user-highlighted (i.e., annotated) text samples.
See the features and benefits table for more details.
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