US 11,860,917 B1
Catalog adoption in procurement
Manisha Dubey, New Delhi (IN); Suket Kumar Jain, Maharashtra (IN); Rajnikant Dutt, New Delhi (IN); Kanakalata Narayanan, Bangalore (IN); Siddesha Swamy, Bangalore (IN); Ranjan Kumar Jena, Odisha (IN); and Manish Sharma Kolachalam, Bangalore (IN)
Assigned to Accenture Global Solutions Limited, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Aug. 30, 2022, as Appl. No. 17/899,318.
Int. Cl. G06F 16/30 (2019.01); G06F 16/33 (2019.01); G06N 3/08 (2023.01); G06F 16/34 (2019.01); G06N 3/0442 (2023.01)
CPC G06F 16/3347 (2019.01) [G06F 16/345 (2019.01); G06N 3/08 (2013.01); G06N 3/0442 (2023.01)] 18 Claims
OG exemplary drawing
 
1. A system comprising:
a processor;
a memory in communication with the processor, the memory storing a plurality of instructions executable by the processor to cause the system to:
receive a non-catalog query from a user interface;
compare the non-catalog query with a plurality of catalog data vector embeddings stored in a domain corpus using a similarity machine learning model comprising a Siamese neural network;
map the non-catalog query to a semantically similar catalog data vector embedding of the plurality of catalog data vector embeddings using the similarity machine learning model;
retrieve an item entry from a data store using the semantically similar catalog data vector embedding, wherein the item entry comprises a description and a supplier of an item;
generate a response to the non-catalog query comprising the retrieved item entry; and
transmit the response to the user interface.