Patent ID: 11861536
Assignee: COUPA SOFTWARE INCORPORATED
Field: IT methods for management (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method comprising:
using a spend management computer system (SMCS) instance among a plurality of SMCS instances in a region, the SMCS instance of the region being communicatively coupled to a first computer of a particular customer among a plurality of customers, importing from one or more ERP systems into the SMCS instance spend data comprising a plurality of spend data lines and loading the spend data previously created by both the first computer of the particular customer and second computers of the plurality of customers from the SMCS instance and a plurality of other SMCS instances in the region to regional data storage;
using a trained deep learning classifier of the SMCS instance to classify the spend data lines of all spend data in the regional data storage in a set of standard spend categories of a taxonomy having a plurality of hierarchical levels to produce a classification mapping at the regional data storage, the trained deep learning classifier being programmed to perform sequence classification using a trained long short-term memory recurrent neural network (LSTM/RNN) being programmed using word vector representations and embedding layers to predict a category for an input sequence, the LSTM/RNN having been trained based on actual or synthetically generated spend data lines with corresponding spend category labels;
executing the sequence classification continuously as new spend data lines are received from the SMCS instances in the region and stored in the regional data storage, and updating the classification mapping at the regional data storage;
computing a first plurality of aggregates of monetary amounts from a first set of classified spend data lines associated with the particular customer;
computing a second plurality of aggregates of monetary amounts from a second set of classified spend data lines associated with a community of the plurality of customers;
creating a plurality of global spend aggregates based on the first plurality of aggregates and the second plurality of aggregates, storing the global spend aggregates in global data/object storage, and building indexes in a global indexing system that is coupled to the global data/object storage;
receiving, at the SMCS instance of the region, from the first computer of the particular customer among the plurality of customers, a request for an optimization recommendation, and in response thereto, the SMCS instance of the region accessing the global indexing system to obtain the first plurality of aggregates and the second plurality of aggregates;
comparing the first plurality of aggregates of monetary amounts and the second plurality of aggregates of monetary amounts; and
sending, to the first computer of the particular customer, responsive to the request for the optimization recommendation, instructions for presenting the optimization recommendation.