公开(公告)号：US20240427783A1

公开(公告)日：2024-12-26

申请号：US18828385

申请日：2024-09-09

Applicant: Palantir Technologies Inc.

Inventor： Elliot Hirsch ,  Johannes Beil ,  Lauren Brown ,  Nicolas Prettejohn ,  Paul Baseotto

IPC: G06F16/2458 ,  G06F16/248

Abstract: A fuzzy matching system matching data records in one or more data sets based on user-customized selection of multiple fuzzy matching algorithms. Possible matches may be displayed to a user, who provides feedback on the accuracy of the matches, which may then be used by a machine learning algorithm to update weightings and parameters of the multiple fuzzy matching algorithms, such as based on machine learning analysis of the matching results and the user feedback.

公开(公告)号：US12111839B1

公开(公告)日：2024-10-08

申请号：US18333975

申请日：2023-06-13

Applicant: Palantir Technologies Inc.

Inventor： Elliot Hirsch ,  Johannes Beil ,  Lauren Brown ,  Nicolas Prettejohn ,  Paul Baseotto

IPC: G06F7/00 ,  G06F16/2458 ,  G06F16/248

CPC classification number: G06F16/2468 ,  G06F16/248

Abstract: A fuzzy matching system matching data records in one or more data sets based on user-customized selection of multiple fuzzy matching algorithms. Possible matches may be displayed to a user, who provides feedback on the accuracy of the matches, which may then be used by a machine learning algorithm to update weightings and parameters of the multiple fuzzy matching algorithms, such as based on machine learning analysis of the matching results and the user feedback.

公开(公告)号：US11720580B1

公开(公告)日：2023-08-08

申请号：US17683986

申请日：2022-03-01

Applicant: Palantir Technologies Inc.

Inventor： Elliot Hirsch ,  Johannes Beil ,  Lauren Brown ,  Nicolas Prettejohn ,  Paul Baseotto

IPC: G06F7/00 ,  G06F16/2458 ,  G06F16/248

CPC classification number: G06F16/2468 ,  G06F16/248

Abstract: A fuzzy matching system matching data records in one or more data sets based on user-customized selection of multiple fuzzy matching algorithms. Possible matches may be displayed to a user, who provides feedback on the accuracy of the matches, which may then be used by a machine learning algorithm to update weightings and parameters of the multiple fuzzy matching algorithms, such as based on machine learning analysis of the matching results and the user feedback.