Systems and methods for classification of data streams
AssigneeArchitecture Technology Corporation
InventorsScott Aloisio, Paul Nicotera
Life of this patent
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Abstract
Disclosed herein are embodiments of systems, methods, and apparatus that execute classification techniques to enable high-quality analysis of ingest data by interpreting and categorizing disparate data points of the ingest data. The execution of the classification techniques leads to isolation of intrinsic properties of each data point to represent the essence of what the overall ingest data indicates. The classification techniques further enables classification of the ingest data, which is unencumbered by any ingest data format changes, such as ordering of data components, encoding, or properties associated with the ingest data that are likely to change without altering meaning conveyed by the ingest data.
Claims20
A computer implemented method comprising:
- receiving, by a computer, a plurality of unstructured data streams from a plurality of data sources;
- for each respective unstructured data stream:
- formatting, by the computer, the unstructured data stream to normalize the unstructured data stream according to a data format;
- and
- generating, by the computer, a set of atomic level data points parsed from the unstructured data stream based upon the data format;
- identifying, by the computer, a common attribute for the sets of atomic level data points parsed from the plurality of unstructured data streams by clustering the sets of atomic level data points to generate a cluster of atomic level data points for the common attribute;
- and
- generating, by the computer, an intermediate representation based upon each common attribute identified by the computer for the plurality of unstructured data streams from the plurality of data sources.
A system comprising:
- a non-transitory storage medium configured to store a plurality of data formats;
- and
- a computer comprising a processor configured to:
- receive a plurality of unstructured data streams from a plurality of data sources;
- for each respective unstructured data stream:
- format the unstructured data stream to normalize the unstructured data stream according to a data format in the database;
- and
- generate a set of atomic level data points parsed from the unstructured data stream based upon the data format;
- identify a common attribute for the set of atomic level data points parsed from the plurality of unstructured data streams, wherein the processor clusters the sets of atomic level data points to generate a cluster of atomic level data points for the common attribute;
- and
- generate an intermediate representation based upon each common attribute identified by the computer for the plurality of unstructured data streams from the plurality of data sources.
Dependencies are inferred from the claim text.