| CPC H04L 63/0435 (2013.01) [G06F 16/2425 (2019.01); G06N 20/00 (2019.01)] | 14 Claims |

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1. A method for generating queries by Machine Learning (ML) models, the method comprising:
generating, by an ML model, a query upon receiving a data trigger associated with an event, based on a domain of the event and a dynamic knowledge graph associated with the domain; and
receiving, by the ML model, a response corresponding to the query in a pre-defined encoded format, wherein the dynamic knowledge graph evolves based on the response;
iteratively performing:
generating, by the ML model, a subsequent query based on the response received for the query and the evolved dynamic knowledge graph, wherein the query immediately precedes the subsequent query;
receiving, by the ML model, a response for the subsequent query in the pre-defined encoded format;
determining, by the ML model, whether the response culminates the current iteration; and
performing, by the ML model, one of:
generating a second subsequent query succeeding the subsequent query, when the response does not culminate the current iteration; and
terminating the iteration when the response culminates the current iteration.
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