Data Classification

Data Classification and Thematic Analysis are machine learning techniques that address the challenges of pattern recognition, by assigning categories, and values to text or documents being analyzed, based on domain-specific models. Specialized classifier models are trained using a combination of Data Dictionaries, Semantic Graphs, data residing in files, databases or any storage medium. They are smart enough to recognize parts of speech or phrases and can be easily made to understand technical terms, medical or legal jargon to infer meaning based on key terms and content similarity.

Classification services make it possible for Cognitive AI to discover, organize, and retrieve data based on similar content, unique features, or semantic meaning. They can also be used to establish intent or sentiment in a body of text and predict features that are unknown or may appear in the future. Classification and Thematic Analysis have broad application in decision support systems, legal due diligence, direct marketing, regulatory compliance or data privacy, insurance, fraud detection and medical diagnosis.