Search in concepts which is hidden or unknown via the search query. Unsupervised learning in 200 million lines from 2 million PubMed articles used to create the Semantic clusters.
Concept search is different from keyword search as it will return the related concepts, keywords.
NaturalText partnered with LexAce to bring Natural Language Understanding and Language Generation capabilites for Judgments
Features include generation of similar judgments when viewing a judgment, generating headnotes, unsupervised tagging of dates, places for making the understanding easier.
NaturalText's Machine Learning Algorithms can process Scientific Papers, Bio Sequences to find patterns and help scientists, researchers to advance their research.
NaturalText's Machine Learning Algorithms can combine various data formats, cross verify for incorrect information, help companies to know more from the data
NaturalText's Artificial Learning Tool based on multiple algorithms is developed to learn, infer, reason with the facts. It can make implicit facts as explicit and show new facts generated from existing data. Tool can show the existing data in different ways.
NaturalText's state of the art Graphical Framework is the base for Machine Learning tasks.