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案件記録

SYSTEMS AND METHODS FOR MACHINE LEARNING MODELS FOR ENTITY RESOLUTION

発明審査中
3閲覧数
21請求項 · 4 独立
§ Ⅰ

案件概要

発明者

Jyotiwardhan PATIL; Eric CARLSON; Cole LEAHY; Bradley S. TOFEL; Vinay GOEL; Nicholas GORSKI

IPC分類

G6F 16/28G6F 11/14G6F 16/18G6F 16/22G6F 16/25G6N 20/

CPC分類

G6F16/288G6F11/1451G6F16/1873G6F16/2228G6F16/258G6N20/G6F2201/80G6F2201/84

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.

原文(中国語)

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.

外部リソース