Invention Grant
- Patent Title: Systems and methods for machine learning models for entity resolution
-
Application No.: US17364651Application Date: 2021-06-30
-
Publication No.: US11321366B2Publication Date: 2022-05-03
- Inventor: Jyotiwardhan Patil , Eric Carlson , Cole Leahy , Bradley S. Tofel , Vinay Goel , Nicholas Gorski
- Applicant: Grand Rounds, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Grand Rounds, Inc.
- Current Assignee: Grand Rounds, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Finnegan, Henderson, Farabow, Garrett & Dunner, LLP
- Main IPC: G06F16/00
- IPC: G06F16/00 ; G06F16/28 ; G06F16/18 ; G06F16/25 ; G06F11/14 ; G06N20/00

Abstract:
Methods, systems, and computer-readable media for linking multiple data entities. The method collects a snapshot of data from one or more data sources and converts it into a canonical representation of records expressing relationships between data elements in the records. The method next cleans the records to generate output data of entities by grouping chunks of records using a machine learning model. The method next ingests the output data of entities to generate a versioned data store of the entities and optimizes versioned data store for real-time data lookup. The method then receives a request for data pertaining to a real-world entity and presenting relevant data from the versioned data store of entities.
Public/Granted literature
- US20220004568A1 SYSTEMS AND METHODS FOR MACHINE LEARNING MODELS FOR ENTITY RESOLUTION Public/Granted day:2022-01-06
Information query