Achieve a deep, automated understanding of complex documents
Conventional Text Analytics enable a first level of automatic understanding of unstructured content, achieved through its ability to extract mentions of entities and concepts, assign general categories or identify the polarity of opinions and facts that appear in the text. However, these isolated information elements do not reflect the wealth of information provided by these documents and impose limitations when it comes to finding, relating or analyzing them automatically.
Deep Semantic Analytics represents a step beyond conventional text analytics by providing features such as snippet-level granular categorization, detection of complex patterns, and extraction of semantic relationships between information elements in the document.
