the invention is a process , system , workflow system for data retrieval processes , software , web site , service and saas created to support a data retrieval process from various document types to custom or preset retrieval data structures . the program supports manual , automatic and semiautomatic data retrieval using its internal features or external add - ons . it links data points in the structure to the corresponding data points in the document , stores documents , structures and links between them and outputs results in various formats . links between a document and a retrieval data structure are established either automatically or manually by the user . after all required links are set , results can be retrieved from the program as an xml structure with required data or as a pdf or html , in ms office formats and others containing a / the retrieval data structure , the original document or both with links between corresponding data points . the system incorporates a text mining engine , which provides automatic information retrieval capabilities . the engine implements text mining technology that is based on evolutionary bayesian ontology classification . this technology uses bayesian ontology for modeling the problem &# 39 ; s domain and applies evolutionary search for the most plausible classification decision . the ability to learn from data is a key feature of bayesian ontology , and for our embodiment . the complexity and size of semantic and format dependencies between elements in a natural language text is too high for analytical descriptions . plus , we intend to save the user the trouble of building their own data retrieval models . instead , we rely on an algorithm that automatically links user &# 39 ; s data selections to the closest categories in pre - built ontologies and generates selection specific classifiers . every individual ontology keeps learning from user corrections during its life cycle . the system is specifically built with the ability to accumulate data models learned from various types of documents . the more documents have been processed by the system , the higher generalization capabilities it possesses for automatic processing of new , unseen documents .