Method for automatically determining target entities from unstructured conversation using natural language understanding

One or more non-transitory computer-readable storage medium storing the one or more sequence of instructions for automatically parsing an unstructured conversation using natural language processing to determine target entities for an engagement activity, which when executed by a processor cause:

• obtaining at least one conversation associated with an asset between a plurality of entities using a dialogue manager from at least one communication channels;
• parsing said at least one unstructured conversation associated with said asset using a natural language processing (NLP) model to obtain a target information associated with said asset;
• extracting at least one attribute of a plurality of target entities from said target information associated with said asset using a natural language understanding (NLU) model of domain of said at least one unstructured conversation;
• generating, using said at least one attribute of said plurality of target entities, a definition of a cohort and at least one criteria for curation of said cohort for said asset by converting said at least one unstructured conversation into a structured target information, wherein said definition of said cohort comprises said at least one attribute of said plurality of target entities;
• and
• determining, a size and characteristics of said plurality of target entities in said cohort using said definition of said cohort and said at least one criteria for cohort curation for said asset for an engagement activity.

A system for automatically parsing an unstructured conversation using natural language processing to determine target entities for an engagement activity, the system comprising:

• a processor;
• a memory that stores set of instructions, which when executed by the processor, causes to perform:
• obtaining at least one unstructured conversation associated with an asset between a plurality of entities using a dialogue manager from at least one communication channels;
• parsing said at least one unstructured conversation associated with said asset using a natural language processing (NLP) model to obtain a target information associated with said asset;
• extracting at least one attribute of a plurality of target entities from said target information associated with said asset using a natural language understanding (NLU) model of domain of said at least one unstructured conversation;
• generating, using said at least one attribute of said plurality of target entities, a definition of a cohort and at least one criteria for curation of said cohort for said asset by converting said at least one unstructured conversation into a structured target information, wherein said definition of said cohort comprises said at least one attribute of said plurality of target entities;
• and
• determining a size and characteristics of said plurality of target entities using said definition of said cohort and said at least one criteria for cohort curation for said asset for an engagement activity.