検索に戻る
案件記録

Techniques for Dynamic Data Validation

発明審査中
20請求項 · 3 独立
§ Ⅰ

案件概要

出願人

UNITEDHEALTH GROUP, INCORPORATED

発明者

Amy L. Neftzger; Erin H. Macphaul; Shashank Kapoor; Jatin Sachdeva; Krystine D. Mahmood; Mayank Kumar

IPC分類

G6Q 40/8

CPC分類

G6Q40/8

Techniques for dynamic data validation are disclosed herein. An example computer-implemented method includes receiving entity data associated with an entity, the entity data including locations of the entity at respective times. The method further includes determining, by executing a dynamic period algorithm, periods based on the entity data; and applying a machine learning (ML) model to the entity data and the periods. Applying the ML model includes determining, for at least one period, one or more confidence values associated with each location at the respective times included in the period based on (i) a frequency associated with each location and (ii) a period distance value relating a current time to the period. The ML model also outputs a ranking for each location included in the period based on the one or more confidence values. The method further includes generating a data object indicating one or more of the ranked locations.

原文(中国語)

Techniques for dynamic data validation are disclosed herein. An example computer-implemented method includes receiving entity data associated with an entity, the entity data including locations of the entity at respective times. The method further includes determining, by executing a dynamic period algorithm, periods based on the entity data; and applying a machine learning (ML) model to the entity data and the periods. Applying the ML model includes determining, for at least one period, one or more confidence values associated with each location at the respective times included in the period based on (i) a frequency associated with each location and (ii) a period distance value relating a current time to the period. The ML model also outputs a ranking for each location included in the period based on the one or more confidence values. The method further includes generating a data object indicating one or more of the ranked locations.

外部リソース