US 12,333,963 B2
Smart-learning and knowledge retrieval system with integrated chatbots
Gopalakrishnan Venkatasubramanyam, Pleasanton, CA (US)
Filed by Gopalakrishnan Venkatasubramanyam, Pleasanton, CA (US)
Filed on Sep. 4, 2022, as Appl. No. 17/902,885.
Application 17/902,885 is a continuation in part of application No. 16/795,618, filed on Feb. 20, 2020, granted, now 11,468,780.
Prior Publication US 2022/0415202 A1, Dec. 29, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/24 (2019.01); G06F 7/14 (2006.01); G06F 16/9535 (2019.01); G06N 20/00 (2019.01); G09B 7/04 (2006.01)
CPC G09B 7/04 (2013.01) [G06F 7/14 (2013.01); G06F 16/9535 (2019.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer implemented method for providing adaptive and personalized e-learning based on continually, artificially learned unique characteristics of a knowledge seeker, the method employing a smart-learning and knowledge retrieval system executable by at least one processor configured to execute computer program instructions for performing the method, the method comprising:
ingesting data from a plurality of sources in a plurality of formats by the smart-learning and knowledge retrieval system;
merging the ingested data into a knowledge base to create an ontology by the smart-learning and knowledge retrieval system, wherein the ingested data is merged into the knowledge base based on computed strengths of terms found in the plurality of sources from which the data is ingested;
assimilating the merged data to generate experiences from the assimilated data by the smart-learning and knowledge retrieval system;
providing a chatbot platform with a chatbot interface to the knowledge seeker;
receiving a query from the knowledge seeker through said chatbot interface by the smart-learning and knowledge retrieval system;
retrieving one of a generated experience and an experience created based on an artificially intelligent understanding of the received query by the smart-learning and knowledge retrieval system;
sending the retrieved experience to the knowledge seeker in an immersive format via the chatbot interface by the smart-learning and knowledge retrieval system for the knowledge seeker to interact with the sent experience;
receiving feedback from the knowledge seeker via the chatbot interface by the smart-learning and knowledge retrieval system in response to the sent experience;
computing a score for the knowledge seeker continually based on each of the received query and the received feedback by the smart-learning and knowledge retrieval system, thereby artificially learning unique characteristics of the knowledge seeker for measuring an ability of the knowledge seeker to learn and to show continued interest in an e-learning course; and
generating interventions and improved experiences by the smart-learning and knowledge retrieval system to provide adaptive and personalized e-learning to the knowledge seeker based on the computed score for the knowledge seeker.