Computerized systems and methods for graph data modeling
AssigneeVerizon Media Inc.
InventorsTravis Adam Walker, Mohammad Suhale Malang Khader
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Abstract
Systems, methods, and computer-readable media are provided for graph data modeling. In accordance with one implementation, a method is provided that includes operations performed by at least one processor. The operations of the method include receiving raw data and determining a model for the raw data, wherein the model defines the graph structure for the raw data. The method also includes converting the raw data to fit the model, and generating at least a portion of a graph based on the raw data and the model, wherein the graph produces modeled data. The method also includes archiving the graph.
Claims20
A computer-implemented method for converting raw data into graph structures, the method including:
- receiving, by a processor of a graph interface, a batch of raw data from a user device, wherein the batch of raw data includes one or more data types, and wherein the one or more data types correspond with at least one of text files, photos, videos, and audio files;
- determining whether the batch of raw data includes a repeating pattern of data;
- based on determining that the batch of raw data includes a repeating pattern of data, splitting the batch of raw data into individualized segments of raw data;
- determining a model for the individualized segments of raw data, wherein the model defines a graph structure for the individualized segments of raw data, wherein determining the model includes:
- identifying one or more stored models, each of the one or more stored models including at least one of required fields, disallowed fields, and field restrictions;
- and
- determining whether the individualized segments of raw data include one of the required fields, disallowed fields, and field restrictions;
- converting the individualized segments of raw data into modeled data to fit the model;
- and
- sending the modeled data to a receiving entity for generating at least a portion of a graph structure based on the modeled data.
A system for converting raw data into a graph structure, comprising:
- a storage device that stores instructions;
- and
- at least one processor that executes instructions for:
- receiving, by a processor of a graph interface, a batch of raw data from a user device, wherein the batch of raw data includes one or more data types, and wherein the one or more data types correspond with at least one of text files, photos, videos, and audio files;
- determining whether the batch of raw data includes a repeating pattern of data;
- based on determining that the batch of raw data includes a repeating pattern of data, splitting the batch of raw data into individualized segments of raw data;
- determining a model for the individualized segments of raw data, wherein the model defines a graph structure for the individualized segments of raw data, wherein determining the model includes:
- identifying one or more stored models, each of the one or more stored models including at least one of required fields, disallowed fields, and field restrictions;
- and
- determining whether the individualized segments of raw data include one of the required fields, disallowed fields, and field restrictions;
- converting the individualized segments of raw data into modeled data to fit the model;
- and
- sending the modeled data to a receiving entity for generating at least a portion of a graph structure based on the modeled data.
A non-transitory computer-readable medium storing instructions, the instructions configured to cause at least one processor to perform operations comprising:
- receiving, by a processor of a graph interface, a batch of raw data from a user device, wherein the batch of raw data includes one or more data types, and wherein the one or more data types correspond with at least one of text files, photos, videos, and audio files;
- determining whether the batch of raw data includes a repeating pattern of data;
- based on determining that the batch of raw data includes a repeating pattern of data, splitting the batch of raw data into individualized segments of raw data;
- determining a model for the individualized segments of raw data, wherein the model defines a graph structure for the individualized segments of raw data, wherein determining the model includes:
- identifying one or more stored models, each of the one or more stored models including at least one of required fields, disallowed fields, and field restrictions;
- and
- determining whether the individualized segments of raw data include one of the required fields, disallowed fields, and field restrictions;
- converting the individualized segments of raw data into modeled data to fit the model;
- and
- sending the modeled data to a receiving entity for generating at least a portion of a graph structure based on the modeled data.
Dependencies are inferred from the claim text.