Abstract: The present disclosure relates to a method and system for generating question variations to user input. The method comprises receiving a user input comprising at least one sentence from a user. Further, plurality of keywords and associated plurality of features are extracted from the at least one sentence. Thereafter, a plurality of question variations is generated for the user input by using one or more subgraphs identified from a trained knowledge graph based on the plurality of keywords and the associated plurality of features. The plurality of keywords and the associated plurality of features are extracted using rich semantics processing, transformation of words from one form to another and similarity. The one or more subgraphs include an entity specific graph and an action specific graph. The system and method of the present disclosure fetches real time user input and generates probable question variations for the user input.

Abstract: The present disclosure relates to a method and system for generating question variations to user input. The method comprises receiving a user input comprising at least one sentence from a user. Further, plurality of keywords and associated plurality of features are extracted from the at least one sentence. Thereafter, a plurality of question variations is generated for the user input by using one or more subgraphs identified from a trained knowledge graph based on the plurality of keywords and the associated plurality of features. The plurality of keywords and the associated plurality of features are extracted using rich semantics processing, transformation of words from one form to another and similarity. The one or more subgraphs include an entity specific graph and an action specific graph. The system and method of the present disclosure fetches real time user input and generates probable question variations for the user input.

Abstract: This disclosure relates generally to natural language processing, and more particularly to system and method for generating named entities. In one embodiment, a method is provided for generating named entities. The method includes extracting a plurality of named entities in a primary language from a plurality of digital content in the primary language, transliterating each of the plurality of named entities in the primary language to a set of possible named entities in a secondary language, determining a correct named entity in the secondary language from among the set of possible named entities in the secondary language, and generating a named entity in a subsequent secondary language corresponding to the correct named entity in the secondary language. It should be noted that the plurality of named entities in the primary language are named entities in the subsequent secondary language, and the subsequent secondary language is related to the secondary language.

Abstract: A method and device for extracting images from PDF documents are disclosed. The method includes performing a text recognition process on a PDF document that includes one or more images. The text recognition process replaces the one or more images with a plurality of contiguous newlines. The method further includes storing a location of each of the one or more images within the PDF document based on occurrence of the plurality of contiguous newlines within the PDF document. The method includes converting each page of the PDF document to an image format in order to generate an image document corresponding to the PDF document. The method further includes extracting each of the one or more images from the image document based on the location stored for each of the one or more images within the PDF document.

Abstract: A method and device for extracting images from PDF documents are disclosed. The method includes performing a text recognition process on a PDF document that includes one or more images. The text recognition process replaces the one or more images with a plurality of contiguous newlines. The method further includes storing a location of each of the one or more images within the PDF document based on occurrence of the plurality of contiguous newlines within the PDF document. The method includes converting each page of the PDF document to an image format in order to generate an image document corresponding to the PDF document. The method further includes extracting each of the one or more images from the image document based on the location stored for each of the one or more images within the PDF document.

Abstract: This disclosure relates generally to natural language processing, and more particularly to system and method for generating named entities. In one embodiment, a method is provided for generating named entities. The method includes extracting a plurality of named entities in a primary language from a plurality of digital content in the primary language, transliterating each of the plurality of named entities in the primary language to a set of possible named entities in a secondary language, determining a correct named entity in the secondary language from among the set of possible named entities in the secondary language, and generating a named entity in a subsequent secondary language corresponding to the correct named entity in the secondary language. It should be noted that the plurality of named entities in the primary language are named entities in the subsequent secondary language, and the subsequent secondary language is related to the secondary language.