Abstract: Embodiments of the present disclosure, implements method of extracting relevant sections from a plurality of documents by (a) receiving an input document from a user; (b) converting, the input document to a standard text file; (c) classifying, the standard text file to obtain a labelled text file associated with at least one cluster from a plurality of clusters; (d) extracting, from the labelled text file to obtain a plurality of relevant entities associated with at least one cluster in the plurality of clusters; (e) annotating, the standard text file by the extracted plurality of relevant entities to obtain an annotated enriched text file; (f) identifying, a plurality of section boundaries to obtain a sectioned data; and (g) extracting, relevant sections of the plurality of documents based on the plurality of relationship associated with the set of relevant entities.

Abstract: Embodiments of the present disclosure, implements method of extracting relevant sections from a plurality of documents by (a) receiving an input document from a user; (b) converting, the input document to a standard text file; (c) classifying, the standard text file to obtain a labelled text file associated with at least one cluster from a plurality of clusters; (d) extracting, from the labelled text file to obtain a plurality of relevant entities associated with at least one cluster in the plurality of clusters; (e) annotating, the standard text file by the extracted plurality of relevant entities to obtain an annotated enriched text file; (f) identifying, a plurality of section boundaries to obtain a sectioned data; and (g) extracting, relevant sections of the plurality of documents based on the plurality of relationship associated with the set of relevant entities.