Invention Grant
- Patent Title: Dual deep learning architecture for machine-learning systems
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Application No.: US18405709Application Date: 2024-01-05
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Publication No.: US12277759B2Publication Date: 2025-04-15
- Inventor: Ying Xie , Linh Le
- Applicant: EQUIFAX INC.
- Applicant Address: US GA Atlanta
- Assignee: EQUIFAX INC.
- Current Assignee: EQUIFAX INC.
- Current Assignee Address: US GA Atlanta
- Agency: Kilpatrick Townsend & Stockton LLP
- Main IPC: G06V10/82
- IPC: G06V10/82 ; G06F16/583 ; G06F16/903 ; G06F18/21 ; G06N3/045 ; G06N3/08 ; G06V10/44 ; G06V10/764 ; G06V40/16

Abstract:
Certain aspects involve a machine-learning query system that uses a dual deep learning network to service queries and other requests. In one example, a machine-learning query system services a query received from a client computing system. A dual deep learning network included in the machine-learning query system matches an unstructured input data object, received from the client computing system, to an unstructured reference data object. The matching may include generating an input feature vector by an embedding subnetwork, based on the unstructured input data object. The matching may also include generating an output probability by a relationship subnetwork, based on the input feature vector and a relationship feature vector that is based on the unstructured reference data object. The machine-learning query system may transmit a responsive message to the client system.
Public/Granted literature
- US20240144665A1 DUAL DEEP LEARNING ARCHITECTURE FOR MACHINE-LEARNING SYSTEMS Public/Granted day:2024-05-02
Information query