Dynamic entity model generation from graph data
AssigneeMicrosoft Technology Licensing, LLC
InventorsChristopher L. Mullins, Congyong Su
Life of this patent
Estimating the term…
Abstract
In the present disclosure, systems, methods and devices for dynamically extending a federated graph are provided. Data may be received in a variety of unrelated forms and one or more classification types may be associated with received data. Relationships that link new data input to existing data sets and their associated classification types may be generated and new data input may be incorporated and stored with existing data sets according to generated data relationships. A data set may be sorted, and resources associated with a data set may be retrieved, based on dynamic query types.
Claims20
A method for dynamically extending a federated graph, comprising:
- inspecting, by a processor, data from a resource that comprises at least a first property and a second property;
- determining whether there is an entity attribute type in the federated graph relating to the first property;
- based on determining that there is not an entity attribute type in the federated graph for the first property, generating, using machine learning, a new entity attribute type that did not previously exist in the federated graph;
- and
- generating at least one node in the federated graph for the resource, the at least one node comprising:
- the first property, wherein the first property is associated with the new entity attribute type in the node;
- and
- the second property, wherein the second property is associated with another entity attribute type in the node.
A computer storage medium comprising executable instructions that, when executed by a processor, assist with selectively managing document editing for an enterprise, the computer-readable storage device including instructions executable by the processor for:
- inspecting data from a plurality of resources, wherein each of the plurality of resources comprises a plurality of properties;
- determining, using machine learning, a first type for a first property and a second type for a second property, wherein the first property and the second property are associated with a resource of the plurality of resources;
- associating, using a contextual classification analysis, the first property with the determined first type and the second property with the determined second type;
- generating a skeletal model for a federated graph based on the determined types and properties of the resource;
- receiving corrective input indicating that the determined first type is incorrect, wherein the corrective input comprises a corrective type for the determined first type, wherein the corrective input;
- and
- associating the corrective type with the first property.
A system for dynamically extending a federated graph, comprising:
- at least one processor;
- and
- a memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations, the set of operations comprising:
- inspecting data from a resource that comprises at least a first property and a second property;
- determining whether there is a type the property in a federated graph relating to the first property;
- based on determining that there is not a type in the federated graph for the first property, generating, using machine learning, a new type that did not previously exist in the federated graph;
- and
- generating at least one node in the federated graph for the resource, the at least one node comprising:
- the first property, wherein the first property is associated with the new type in the node;
- and
- the second property, wherein the second property is associated with another entity attribute type in the node.
Dependencies are inferred from the claim text.