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1. US20200004834 - Integration of artificial intelligence-based data classification processes with a procurement system to relativize an entity score

Office
United States of America
Application Number 16020670
Application Date 27.06.2018
Publication Number 20200004834
Publication Date 02.01.2020
Grant Number 11030200
Grant Date 08.06.2021
Publication Kind B2
IPC
G06F 16/2457
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
24Querying
245Query processing
2457with adaptation to user needs
G06Q 10/08
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
10Administration; Management
08Logistics, e.g. warehousing, loading, distribution or shipping; Inventory or stock management, e.g. order filling, procurement or balancing against orders
G06F 9/451
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
44Arrangements for executing specific programs
451Execution arrangements for user interfaces
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G06F 16/28
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
28Databases characterised by their database models, e.g. relational or object models
CPC
G06F 9/451
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
44Arrangements for executing specific programs
451Execution arrangements for user interfaces
G06F 16/24578
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
24Querying
245Query processing
2457with adaptation to user needs
24578using ranking
G06F 16/285
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
28Databases characterised by their database models, e.g. relational or object models
284Relational databases
285Clustering or classification
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G06Q 10/087
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
10Administration; Management
08Logistics, e.g. warehousing, loading, distribution or shipping; Inventory or stock management, e.g. order filling, procurement or balancing against orders
087Inventory or stock management, e.g. order filling, procurement, balancing against orders
Applicants Coupa Software Incorporated
Inventors Ahmad Sadeddin
Scott Harris
Yutaka Hosoai
Agents Baker Botts L.L.P.
Title
(EN) Integration of artificial intelligence-based data classification processes with a procurement system to relativize an entity score
Abstract
(EN)

Technologies for computing a relativized entity score include generating first actionable output that identifies a particular supplier and an intrinsic score for the particular supplier that is calculated using intrinsic factor data for the particular supplier, where the intrinsic factor data is obtained from a plurality of instances of procurement software; determining a set of weights using peer spend data of a set of peer suppliers, where the set of peer suppliers is identified based on a spend label that is associated with the peer spend data by an artificial intelligence-based process; applying the set of weights to a set of intrinsic scores for the set of peer suppliers to produce a set of peer scores, where a weight in the set of weights is calculated using the peer spend data; aggregating the set of peer scores to produce an aggregate peer score; generating second actionable output, where the second actionable output modifies or supplements the first actionable output based on a comparison of the intrinsic score for the particular supplier to the aggregate peer score, where the method is performed by one or more computing devices.