US 2025/0156758 A1Published application

Devices, data structure, and computer-implemented methods for machine learning using semantic technologies

OwnerChristian Simonis, Christoph Zimmer +1inventors

InventorsChristian Simonis, Christoph Zimmer, Irlan Grangel Gonzalez

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Abstract

Devices, data structure, and computer-implemented methods for machine learning. A method for machine learning includes providing a data structure of a database, which data structure includes a set of nodes and a set of relations, and a set of tuples. Each respective tuple includes at least two nodes, and at least one relation. The method includes predicting a plurality of tuples depending on the data structure, wherein each respective tuple includes at least two nodes and at least one relation, predicting, whether the respective tuples of the plurality of tuples classifies as a member of the set of tuples, selecting a tuple from the plurality of tuples depending on the uncertainties predicted for the respective tuples, acquiring a label that indicates whether the selected tuple classifies as a member of the set of tuples, and adding the selected tuple to the set of tuples based on the label.

Claims14

Dependent claims

A computer-implemented method for machine learning, the method comprising the following steps:

providing a data structure of a database, the data structure including a set of nodes, the set of nodes including:
(i) a set of entities or (ii) a set of subjects and objects, the data structure further including a set of relations including:
(i) a set of edges or (ii) a set of predicates, and the data structure further including a set of tuples, wherein each respective tuple of the set of tuples includes at least two nodes of the set of nodes, and at least one relation of the set of relations, which includes:
(i) two entities of the set of entities, and an edge of the set of edges, or (ii) a subject and an object of the set of subjects and objects, and a predicate of the set of predicates;
predicting a plurality of tuples depending on the data structure, wherein each respective tuple of the plurality of tuples includes at least two nodes of the set of nodes, and at least one relation of the set of relations, which includes:
(i) two entities of the set of entities, and an edge of the set of edges, or (ii) a subject and an object of the set of subjects and objects, and a predicate of the set of predicates;
predicting, for each respective tuple of the plurality of tuples, an uncertainty about whether the respective tuple of the plurality of tuples classifies as a member of the set of tuples or not;
selecting a tuple from the plurality of tuples depending on the uncertainties predicted for the respective tuples;
acquiring a label that indicates whether the selected tuple classifies as a member of the set of tuples or not;
and
(i) adding the selected tuple to the set of tuples when the label indicates that the selected tuple classifies as member of the set of tuples, or (ii) not adding the selected tuple to the set of tuples otherwise or when the label indicates that the selected tuple classifies not as member of the set of tuples.

8 more elements

A device for machine learning, comprising:

at least on processor;
and
at least one memory, wherein the at least one processor is configured to execute instructions that, when executed by the at least one processor, cause the device to perform:
providing a data structure of a database, the data structure including a set of nodes, the set of nodes including:
(i) a set of entities or (ii) a set of subjects and objects, the data structure further including a set of relations including:
(i) a set of edges or (ii) a set of predicates, and the data structure further including a set of tuples, wherein each respective tuple of the set of tuples includes at least two nodes of the set of nodes, and at least one relation of the set of relations, which includes:
(i) two entities of the set of entities, and an edge of the set of edges, or (ii) a subject and an object of the set of subjects and objects, and a predicate of the set of predicates,
predicting a plurality of tuples depending on the data structure, wherein each respective tuple of the plurality of tuples includes at least two nodes of the set of nodes, and at least one relation of the set of relations, which includes:
(i) two entities of the set of entities, and an edge of the set of edges, or (ii) a subject and an object of the set of subjects and objects, and a predicate of the set of predicates,
predicting, for each respective tuple of the plurality of tuples, an uncertainty about whether the respective tuple of the plurality of tuples classifies as a member of the set of tuples or not,
selecting a tuple from the plurality of tuples depending on the uncertainties predicted for the respective tuples,
acquiring a label that indicates whether the selected tuple classifies as a member of the set of tuples or not, and
(i) adding the selected tuple to the set of tuples when the label indicates that the selected tuple classifies as member of the set of tuples, or (ii) not adding the selected tuple to the set of tuples otherwise or when the label indicates that the selected tuple classifies not as member of the set of tuples;
wherein the at least one memory is configured to store the instructions.

11 more elements

A non-transitory computer-readable medium on which is stored computer-readable instructions that, when executed by the computer, cause the computer to perform the following steps:

providing a data structure of a database, the data structure including a set of nodes, the set of nodes including:
(i) a set of entities or (ii) a set of subjects and objects, the data structure further including a set of relations including:
(i) a set of edges or (ii) a set of predicates, and the data structure further including a set of tuples, wherein each respective tuple of the set of tuples includes at least two nodes of the set of nodes, and at least one relation of the set of relations, which includes:
(i) two entities of the set of entities, and an edge of the set of edges, or (ii) a subject and an object of the set of subjects and objects, and a predicate of the set of predicates;
predicting a plurality of tuples depending on the data structure, wherein each respective tuple of the plurality of tuples includes at least two nodes of the set of nodes, and at least one relation of the set of relations, which includes:
(i) two entities of the set of entities, and an edge of the set of edges, or (ii) a subject and an object of the set of subjects and objects, and a predicate of the set of predicates;
predicting, for each respective tuple of the plurality of tuples, an uncertainty about whether the respective tuple of the plurality of tuples classifies as a member of the set of tuples or not;
selecting a tuple from the plurality of tuples depending on the uncertainties predicted for the respective tuples;
acquiring a label that indicates whether the selected tuple classifies as a member of the set of tuples or not;
and
(i) adding the selected tuple to the set of tuples when the label indicates that the selected tuple classifies as member of the set of tuples, or (ii) not adding the selected tuple to the set of tuples otherwise or when the label indicates that the selected tuple classifies not as member of the set of tuples.

8 more elements

A non-transitory computer-readable medium on which is stored a data structure, the data structure comprising a set of nodes including a set of entities or a set of subjects and objects, the data structure further comprising a set of relations including a set of edges or a set of predicates, and wherein the data structure further comprises a set of tuples, wherein each respective tuple of the set of tuples includes at least two nodes of the set of nodes, and at least one relation of the set of relations which include:

(i) two entities of the set of entities and an edge of the set of edges, or (ii) a subject and an object of the set of subjects and object, and a predicate of the set of predicates, wherein the data structure is configured to include a plurality of tuples that are predicted depending on the data structure, wherein each respective tuple of the plurality of tuples includes at least two nodes of the set of nodes, and at least one relation of the set of relations, which include:
(i) two entities of the set of entities and an edge of the set of edges, or (ii) a subject and an object of the set of subjects and objects, and a predicate of the set of predicates, and wherein the data structure is further configured to include an uncertainty about whether each respective tuple of the plurality of tuples classifies as a member of the set of tuples or not, wherein the data structure is configured to include a tuple that is selected from the plurality of tuples depending on the uncertainties predicted for the respective tuples, wherein the data structure is configured to include a label that indicates whether the selected tuple classifies as a member of the set of tuples or not, wherein the data structure is configured for:
(i) adding the selected tuple to the set of tuples when the label indicates that the selected tuple classifies as member of the set of tuples, or (ii) not adding the selected tuple to the set of tuples otherwise, or when the label indicates that the selected tuple classifies not as member of the set of tuples.

Dependencies are inferred from the claim text.