Abstract: A semantic textual information recognition system is provided. The system includes a memory configured to receive a plurality of text elements along with respective text element coordinates. The system includes a processor operatively coupled to the memory, wherein the processor includes a spatial reconstruction module configured to identify the plurality of text elements on an information axis based on the text element coordinates. The processor also includes a semantic clustering module configured to determine a plurality of semantic clusters of the plurality of text elements by calculating a proximity matrix using the plurality of text elements on the same information axis and a semantic data model. The processor further includes a rank clustering module configured to generate a plurality of rank clusters by ranking the plurality of semantic clusters. The processor further includes a machine learning module configured to update the semantic data model based on the feature set.

Abstract: A system and method for generating a virtual assistant is disclosed. The system for generating a virtual assistant includes a configuration subsystem configured to receive one or more parameters from a document. The configuration subsystem is also configured to serialize the one or more parameters automatically extracted from the document and generate a structured object based on the one or more serialized parameters. The configuration unit is further configured to embed all validation criteria specified in the document. The system for generating a virtual assistant also includes a virtual assistant generator operatively coupled with the configuration subsystem and configured to analyze the structured object. The virtual assistant generator is also configured to automatically generate a virtual assistant based on an analyzed structured object.