ATTENTION-BASED DEEP NEURAL ARCHITECTURES FOR MULTI-POINT RESPONSE GENERATION IN VIRTUAL BUSINESS ASSISTANT AI ENGINES

Abstract: in one aspect, a computerized-method for implementing a unified model that responds to an incoming customer message or request, comprising: given a user input message, u: identifying a response, r, that is to be sent to the customer, identifying a business notification, b, that is to be sent to the staff at the business, basing the response, r, and the business notification, b, on a common template or a business-specific template or a canned response defined by the business; wherein a unique (r,b) pair comprises a potential response to the input user message, u, storing a plurality of (r,b) pairs in a document store that is accessible through an information retrieval system; alongside the plurality of (r,b) pairs, storing a set of examples and a set of variations of the customer query, q, for which each (r,b) pair of the plurality of (r,b) pairs is the appropriate response; given a query, q: providing a plurality of corresponding (q,r,b) triples.

Inventor(s): SRIVATSAN LAXMAN, SRAVANTHI MUTYALA, HRUDAY GOWDA, SRIKHAR PADMANABHAN, SUPRIYA RAO

CPC Classification: G06Q30/015 (Customer relationship services)

Search for rejections for patent application number 20250173733