Abstract: Exemplary systems and methods are provided for generating natural language responses to input queries by receiving a first input query; determining one or more of characteristics of the input query; selecting, from a plurality of response modules, one or more response modules based on the one or more characteristics of the input query and one or more metrics associated with each of the one or more response modules, wherein each response module of the plurality of response modules comprises a plurality of machine learning models for generating a response to the input query; and generating one or more responses to the first input query using the selected one or more response modules.

Abstract: Existing systems for document processing are either based on a supervised approach using annotated tags, and these systems identify section-based data from the unstructured documents without considering the statistical variations in content, which results in highly inaccurate content extraction. The disclosure herein generally relates to document processing, and, more particularly, to method and system for document indexing and retrieval. The system provides a mechanism to correlate unique words in a document with different topics identified in the document, based on a word pattern identified from the document. The correlations are captured in a knowledge graph, and can be further used in applications such as but not limited to document retrieval.

Abstract: Existing systems for document processing are either based on a supervised approach using annotated tags, and these systems identify section-based data from the unstructured documents without considering the statistical variations in content, which results in highly inaccurate content extraction. The disclosure herein generally relates to document processing, and, more particularly, to method and system for document indexing and retrieval. The system provides a mechanism to correlate unique words in a document with different topics identified in the document, based on a word pattern identified from the document. The correlations are captured in a knowledge graph, and can be further used in applications such as but not limited to document retrieval.