Papyrus Recognition Server supports self-learning modules for the classification and data extraction of business documents. Powered by the IDEX Engine, the Recognition Server offers a broad range of possibilities for application in the field of automated sorting and distribution of electronic documents, fax and paper mail. For data extraction, the Recognition Server can identify unstructured and structured documents with great reliability. This process is based on the latest methods in pattern recognition and represents the most current standards in the fields of print analysis (OCR, ICR, Voting), associative databases, fuzzy logic and neural networks.
Mode of Function
Document classification and data extraction can utilize Robotic Process Automation and Artificial Intelligence capabilities in a self-learning User Trained Agent. This process can also include a non-self learning mode.
Document Classification The purpose of the Papyrus Recognition Server for document classification is to enable an automated process of judging incoming data according to selected criteria, sorting them into freely definable categories – thereby making information actually accessible for the company – and forwarding them accurately to those who are in charge of the issue. A typical application would be automated pre-sorting of incoming electronic mail. It is also perfectly suitable for automatic classification of text print in different languages according to language criteria.
Data Extraction The Papyrus Recognition Server extracts and reads all necessary field data from the identified document class. This process can include unstructured layouts – processing documents of unknown format – and structured forms with keywords at predefined positions.