Method for performing dataset operations within a cognitive environment

• US 10,262,264 B2
• Filed: 02/24/2015
• Issued: 04/16/2019
• Est. Priority Date: 06/09/2014
• Status: Active Grant

• Current Assignee: Tecnotree Technologies Incorporated
• Original Assignee: Cognitive Scale Inc (Tecnotree Oyj)
• Inventors: Sanchez, Matthew, Ranatunga, Dilum
• Primary Examiner(s): Wong, Lut
• Application Number:
  US14/629,638
• Publication Number:
  US 20150356426A1
• Time in Patent Office: 1,512 Days
• Field of Search: 706 45
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

A method for performing dataset operations within a cognitive information processing system comprising: receiving data from a plurality of data sources; and, processing the data from the plurality of data sources, the processing the data establishing and maintaining a dynamic data ingestion and enrichment pipeline.

Claims

1. A method for performing dataset operations within a cognitive information processing system environment, the cognitive information processing system environment comprising a cognitive inference and learning system and a cognitive application, the cognitive inference and learning system comprising a cognitive engine, the cognitive engine comprising a dataset engine, the method comprising:

performing cognitive computing operations via the cognitive inference and learning system, the cognitive inference and learning system executing on a hardware processor of an information processing system, the cognitive inference and learning system comprising a cognitive platform, the cognitive inference and learning system and the information processing system providing a cognitive computing function;

receiving data from a plurality of data sources, the plurality of data sources comprising a public data source and a private data source, the public data source comprising publicly available information, the private data source comprising privately managed, company specific information, the public data source comprising at least one of a social data source stored in a social data repository, public data source stored in a public data repository, licensed data source stored in a licensed data repository and proprietary data source stored in a proprietary data repository; and

,

processing the data from the plurality of data sources via the dataset engine, the processing the data establishing and maintaining a dynamic data ingestion and enrichment pipeline, the dataset engine being coupled to a dataset metadata repository, the dataset metadata repository comprising curated data contained in a repository of cognitive graphs, the dataset metadata providing support of versioning of the streams of data received from the plurality of data sources, the processing comprising;

performing data enriching on the data from the plurality of data sources, and

generating a sub-graph based upon the data enriching on the data from the plurality of data sources for incorporation into at least one of a cognitive graph and a private cognitive graph, the data enriching being performed via an enrichment agent, the cognitive graph and the private cognitive graph each comprising a respective machine-readable, declarative memory system, the cognitive graph and the private cognitive graph each comprising a collection of nodes and edges that join pairs of nodes, the cognitive graph storing and learning both episodic memory and semantic memory, the sub-graph comprising a collection of nodes and edges that join pairs of nodes that are next lower than those contained in each of the cognitive graph and the private cognitive graph, the cognitive graph being stored within the repository of cognitive graphs, the cognitive platform being coupled to and communicating with the plurality of data sources, the cognitive graph, the private cognitive graph and a cognitive application, the cognitive inference and learning system using the streams of data from the dataset engine to generate cognitive insights, the cognitive insights comprising a visual data story highlighting user-specific insights, relationships and recommendations; and

,

providing the cognitive insights to a destination, the destination comprising the cognitive application, the cognitive application enabling a user to interact with the cognitive insights, the cognitive application being a cloud-based application, interaction with the cognitive insights being in the form of a response or a query, the response or query being provided to the cognitive inference and learning system, the cognitive inference and learning system providing another cognitive insight in response to the response or query from the user.

2. The method of claim 1, further comprising:

converting ingested data into streams of data for processing by the cognitive information processing system.

3. The method of claim 1, further comprising:

receiving ingested data and performing data enrichment operations on the ingested data.

4. The method of claim 3, further comprising:

invoking an enrichment agent to perform the data enrichment operations on the ingested data.

5. The method of claim 4, wherein:

the plurality of data sources comprise platform data; and

,

the enrichment agent communicates with the platform data.

6. The method of claim 5, wherein:

the platform data comprises a plurality of data sets; and

,

the enrichment agent communicates with the plurality of datasets within the platform data.

7. The method of claim 1, further comprising:

caching a local version of an enriched data stream; and

,

performing incremental ingestion of the enriched data stream.