Invention Grant
- Patent Title: Method and system for learning rules from a data base
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Application No.: US16993995Application Date: 2020-08-14
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Publication No.: US11699076B2Publication Date: 2023-07-11
- Inventor: Csaba Domokos , Daria Stepanova , Jeremy Zieg Kolter , Po-Wei Wang
- Applicant: Robert Bosch GmbH , Carnegie Mellon University
- Applicant Address: DE PA Stuttgart
- Assignee: ROBERT BOSCH GMBH,CARNEGIE MELLON UNIVERSITY
- Current Assignee: ROBERT BOSCH GMBH,CARNEGIE MELLON UNIVERSITY
- Current Assignee Address: DE Stuttgart; US PA Pittsburgh
- Agency: Norton Rose Fulbright US LLP
- Agent Gerard Messina
- Priority: EP 199308 2019.09.24
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; G06N5/025

Abstract:
A system and computer implemented method for learning rules from a data base including entities and relations between the entities, wherein an entity is either a constant or a numerical value, and a relation between a constant and a numerical value is a numerical relation and a relation between two constants is a non-numerical relation. The method includes: deriving aggregate values from said numerical and/or non-numerical relations; deriving non-numerical relations from said aggregate values; adding said derived non-numerical relations to the data base; constructing differentiable operators, wherein a differentiable operator refers to a non-numerical or a derived non-numerical relation of the data base, and extracting rules from said differentiable operators.
Public/Granted literature
- US20210089894A1 METHOD AND SYSTEM FOR LEARNING RULES FROM A DATA BASE Public/Granted day:2021-03-25
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