Abstract: A method of identifying relevant keywords from a document is disclosed. The method includes splitting text of the document into a plurality of keyword samples, such that each of the plurality of keyword samples comprises a predefined number of keywords extracted in a sequence. Further, each pair of adjacent keyword samples in the plurality of samples includes a plurality of common words. The method further includes determining a relevancy score for each of the plurality of keyword samples based on at least one of a trained Convolution Neural Network (CNN) model and a keyword repository. The method further includes classifying keywords from each of the plurality of keyword samples as relevant keywords or non-relevant keywords based on the relevancy score determined for each of the plurality of keyword samples.

Abstract: The present disclosure discloses a method and system for providing response to a user input. The system receives a user input, processes the user input by finding equivalents of the user input and dividing each of the user input and the equivalents into a frame. One or more keywords are generated for each of the one or more frames. Further, each of the one or more frames are classified into one or more domains present in a knowledge graph. Then, one or more objects are determined in each of the corresponding one or more domains based on the corresponding one or more keywords. Further, a processing means is determined for each of the one or more objects based on the metadata of the corresponding one or more objects. The processing means is processed by the system for providing response to the user input.

Abstract: Disclosed herein is a method and system for automating context-based switching between user activities. The method comprises receiving user inputs from users in one or more input modes and based on a predefined score associated with input modes the context of user input is determined. Based on the determined context and one or more predefined activities of users, a predefined first activity is recommended. Further, a deviation from the context associated with the predefined first activity to a context associated with a second activity is detected, based on user input. Since the context is deviated, the second activity is performed upon detecting availability of pre-recorded activities related to second activity. Once the second activity is completed, system switches back to predefined first activity to complete predefined first activity. The system understands context of the user based on user inputs and performs different activities according to users comfort and requirements.

Abstract: A method of identifying relevant keywords from a document is disclosed. The method includes splitting text of the document into a plurality of keyword samples, such that each of the plurality of keyword samples comprises a predefined number of keywords extracted in a sequence. Further, each pair of adjacent keyword samples in the plurality of samples includes a plurality of common words. The method further includes determining a relevancy score for each of the plurality of keyword samples based on at least one of a trained Convolution Neural Network (CNN) model and a keyword repository. The method further includes classifying keywords from each of the plurality of keyword samples as relevant keywords or non-relevant keywords based on the relevancy score determined for each of the plurality of keyword samples.

Abstract: The present disclosure discloses a method and system for providing response to a user input. The system receives a user input, processes the user input by finding equivalents of the user input and dividing each of the user input and the equivalents into a frame. One or more keywords are generated for each of the one or more frames. Further, each of the one or more frames are classified into one or more domains present in a knowledge graph. Then, one or more objects are determined in each of the corresponding one or more domains based on the corresponding one or more keywords. Further, a processing means is determined for each of the one or more objects based on the metadata of the corresponding one or more objects. The processing means is processed by the system for providing response to the user input.

Abstract: Systems and methods for inventory control in an establishment are described. The system receives sensor data, planogram data, and image data. Based on the sensor data, the system determines current position of products placed at product support devices (PSD). Further, the current position is compared with predefined arrangement defined in the planogram data. Further, the system determines planogram compliance metric, based on the comparison, indicating deviation of placement of the products. The system further identifies the products in the PSDs based on the image data. Further, a product-count corresponding to each of the products are determined. The product-count of at least one product is compared with corresponding predefined threshold count to determine a product stock-out condition indicating at least one of an out of stock condition and low on stock condition. The system further generates product filling information based on the product stock-out condition.