Deep learning techniques based multi-purpose conversational agents for processing natural language queries

Systems and methods for Deep Learning techniques based multi-purpose conversational agents for processing natural language queries. The traditional systems and methods provide for conversational systems for processing natural language queries but do not employ Deep Learning techniques, and thus are unable to process large number of intents. Embodiments of the present disclosure provide for Deep Learning techniques based multi-purpose conversational agents for processing the natural language queries by defining and logically integrating a plurality of components comprising of multi-purpose conversational agents, identifying an appropriate agent to process one or more natural language queries by a High Level Intent Identification technique, predicting a probable user intent, classifying the query, and generate a set of responses by querying or updating one or more knowledge graphs (322). «To be published with FIG. 3> cintfc DSM 302 Primary Agents 306 318 (layer) General Chatter Box Agent 301 Multi- 307 level hitent AxlayAet Identify IAD Framework 308 Leave Agent Auxiliary Agents caio03941 cato- Q rmEmergencyo 3 Conmpo Medic ,al Agent Health -+o Dialogue Agent net311 - 2 303 -Insurance32 gTimesheet Agent Agent 310 A3ent Ag316 KGnoaewgnt17graph raph2 Mgnager1 Travel Agent 3 13 __Update Agent 321 Auto-QUE Framework 314 KGQA Agent Suggest KGU-NL 35Kniowledge 35Agent 316 KG, Engage Agent 317 Graph(s) 322 Core