Graph query engine for use within a cognitive environment

• US 10,445,317 B2
• Filed: 02/24/2015
• Issued: 10/15/2019
• 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): Beausoliel, Jr., Robert W
• Assistant Examiner(s): Khakhar, Nirav K
• Application Number:
  US14/629,644
• Publication Number:
  US 20150356135A1
• Time in Patent Office: 1,694 Days
• CPC Class Codes: G06F 16/243 Natural language query formulation
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

An apparatus for use within a cognitive information processing system environment comprising: a graph query engine, the graph query engine coupled to receive data from a plurality of data sources, the graph query engine receiving and processing queries and to bridge the queries into a cognitive graph.

Claims

1. An apparatus for use within a cognitive information processing system environment comprising:

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

a cognitive engine, the cognitive engine comprising a graph query engine, the graph query engine coupled to receive data from a plurality of data sources;

a plurality of sourcing agents, the plurality of sourcing agents sourcing multi-site, multi-structured data streams; and

,

a plurality of destination agents, the plurality of destination agents publishing cognitive processed insights to a consumer of cognitive insight data; and

,

a cognitive graph, the cognitive engine generating, accessing and updating the cognitive graph, the graph query engine receiving and processing queries and bridging the queries into the cognitive graph, the cognitive graph being derived from the plurality of data sources, the cognitive graph enabling the cognitive inference and learning system to render cognitive insights, the cognitive insights being based on factual knowledge which is based on observation, the cognitive insights providing a result of anticipating an inner nature of a thing;

the plurality of data sources 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, the cognitive computing function comprising at least one of performing a spatial navigation operation, a machine vision operation and a pattern recognition operation on at least some of the streams of data from the plurality of data sources; and

,

a destination, the destination receiving the cognitive insights, the destination comprising a cognitive application, the cognitive application enabling a user to interact with the cognitive insights, the cognitive application being a cloud-based application.

2. The apparatus of claim 1, wherein

the graph query engine comprises a query component, the query component supporting natural language queries.

3. The apparatus of claim 1, wherein

the graph query engine comprises a translate component, the translate component converting processed queries into a cognitive graph form, the cognitive graph form enabling querying of a target cognitive graph.

4. The apparatus of claim 1, wherein

the graph query engine comprises a bridge component, the bridge component bridging a translated query to a cognitive graph and providing domain-specific responses.

5. The apparatus of claim 1, wherein

the graph query engine comprises a bridging agent, the bridging agent interpreting requests and user context and mapping the requests and user context to an appropriate node and line within the cognitive graph.

6. The apparatus of claim 5, wherein

the plurality of data sources comprise platform data;

and,

the bridging agent communicates with the platform data.

7. The apparatus of claim 6, wherein

the platform data comprises a plurality of data sets;

and,

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

8. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:

providing a cognitive inference and learning system, the cognitive inference and learning system performing a cognitive computing function, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising

a cognitive engine, the cognitive engine comprising a cognitive graph engine,

a plurality of sourcing agents, the plurality of sourcing agents sourcing multi-site, multi-structured data streams;

a plurality of destination agents, the plurality of destination agents publishing cognitive processed insights to a consumer of cognitive insight data; and

,

a cognitive graph;

receiving data from a plurality of data sources, the plurality of data sources comprising 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;

performing a cognitive computing function via the cognitive inference and learning system, the cognitive computing function comprising at least one of performing a spatial navigation operation, a machine vision operation and a pattern recognition operation on at least some of the streams of data from the plurality of data sources;

generating, accessing and updating the cognitive graph via the cognitive engine;

receiving and processing queries;

bridging the queries into the cognitive graph, the cognitive graph being derived from the plurality of data sources, the cognitive graph enabling the cognitive inference and learning system to render cognitive insights, the cognitive insights being based on factual knowledge which is based on observation, the cognitive insights providing a result of anticipating an inner nature of a thing; and

,

providing the cognitive insights to a destination, the destination comprising a cognitive application, the cognitive application enabling a user to interact with the cognitive insights, the cognitive application being a cloud-based application.

9. The non-transitory, computer-readable storage medium of claim 8, wherein the instructions executable by the processor further comprise instructions for:

supporting natural language queries.

10. The non-transitory, computer-readable storage medium of claim 8, wherein the instructions executable by the processor further comprise instructions for:

converting processed queries into a cognitive graph form, the cognitive graph form enabling querying of a target cognitive graph.

11. The non-transitory, computer-readable storage medium of claim 10, wherein the instructions executable by the processor further comprise instructions for:

bridging a translated query to a cognitive graph and providing domain-specific responses.

12. The non-transitory, computer-readable storage medium of claim 8, wherein the instructions executable by the processor further comprise instructions for:

interpreting requests and user context and mapping the requests and user context to an appropriate node and line within the cognitive graph.

13. The non-transitory, computer-readable storage medium of claim 8, wherein:

the plurality of data sources comprise platform data; and

,

a bridging agent communicates with the platform data.

14. The non-transitory, computer-readable storage medium of claim 13, wherein

the platform data comprises a plurality of data sets;

and,

a bridging agent communicates with the plurality of datasets within the platform data.

15. The non-transitory, computer-readable storage medium of claim 8, wherein the computer executable instructions are deployable to a client system from a server system at a remote location.

16. The non-transitory, computer-readable storage medium of claim 8, wherein the computer executable instructions are provided by a service provider to a user on an on-demand basis.

17. A cognitive information processing system environment comprising:

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 travel information, the private data source comprising privately managed, company specific travel information;

a first cognitive inference and learning system executing on a first hardware processor of a first information processing system, the cognitive inference and learning system providing a cognitive computing function, the cognitive inference and learning system comprising a hosted cognitive platform, the hosted cognitive platform comprising a hosted cognitive engine, the hosted cognitive engine comprising a hosted graph query engine, the graph query engine coupled to receive data from a plurality of data sources, the cognitive computing function comprising at least one of performing a spatial navigation operation, a machine vision operation and a pattern recognition operation on at least some of the streams of data from the plurality of data sources, the hosted cognitive engine generating, accessing and updating the hosted cognitive graph;

the hosted graph query engine receiving and processing queries and bridging the queries into the hosted cognitive graph, the hosted cognitive graph being derived from the plurality of data sources;

a second cognitive inference and learning system executing on second hardware processor of a second information processing system, the second cognitive inference and learning system providing a second cognitive computing function, the second cognitive inference and learning system comprising a private cognitive platform, the private cognitive platform comprising a private cognitive engine, the private cognitive engine comprising a private graph query engine, the graph query engine coupled to receive data from a private, company hosted data source, the second cognitive computing function comprising at least one of performing a spatial navigation operation, a machine vision operation and a pattern recognition operation on at least some of the streams of data from the plurality of data sources, the private cognitive engine generating, accessing and updating the private cognitive graph;

the private graph query engine receiving and processing queries and bridging the queries into the private cognitive graph, the private cognitive graph being derived from the private, company hosted data source, the private cognitive platform interacting with the hosted cognitive platform to provide cognitive insights, the cognitive insights being based on factual knowledge which is based on observation, the cognitive insights providing a result of anticipating an inner nature of a thing; and

,

a destination, the destination receiving the cognitive insights, the destination comprising a private cognitive application, the private cognitive application enabling a user to interact with the cognitive insights.

18. The apparatus of claim 17, wherein

the hosted graph query engine and the private graph query engine comprise a respective query component, each respective query component supporting natural language queries.

19. The apparatus of claim 17, wherein

the hosted graph query engine and the private graph query engine comprise a respective translate component, each respective translate component converting processed queries into a cognitive graph form, the cognitive graph form enabling querying of a target cognitive graph.

20. The apparatus of claim 17, wherein

the hosted graph query engine and the private graph query engine comprise a respective bridge component, each respective bridge component bridging a translated query to a cognitive graph and providing domain-specific responses.