Semantically mediated access to knowledge

• US 9,201,905 B1
• Filed: 01/14/2010
• Issued: 12/01/2015
• Est. Priority Date: 01/14/2010
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Kelsey, William David, Blanchard, Duane Lee
• Primary Examiner(s): Jalil, Neveen Abel
• Assistant Examiner(s): TORGRIMSON, TYLER J
• Application Number:
  US12/687,377
• Time in Patent Office: 2,147 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24522 Translation of natural language queries to structured queries
• CPC Class Codes: G06F 16/27 Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
• CPC Class Codes: G06F 7/06 Arrangements for sorting, selecting, merging, or comparing data on individual record carriers

Abstract

The different advantageous embodiments provide a system for positioning data within a network comprising a knowledge manager, a canonical model manager, and a context manager. The knowledge manager is configured to process a query across a number of resources to generate a result. The canonical model manager includes a number of models used to identify relationships between types of information within the number of resources and the query. The context manager is configured to manage the context of the query and the relationships identified by the canonical model manager to position the number of resources for access by the knowledge manager.

Claims

1. A system for positioning data within a network, the system comprising:

a processor configured to execute a knowledge manager configured to receive a query from a querent, the knowledge manager further configured to;

receive the query from the querent, and determine whether the query is in logical form, and responsive to a determination that the query is in logical form, compare entries of the logical form query with canonical models passed from a semantic query engine, and determine whether the entries of the logical form query match entries of the canonical models, and responsive to a determination that the entries of the logical form query match the entries of the canonical models, pass a relational form query to the knowledge manager;

determine whether the query is a session command, and responsive to a determination that the query is a session command, determine whether the querent ends a session, and responsive to a determination that the querent ends the session, the knowledge manager updates all caches, marks all waypoints, generates reports, and clears contexts; and

process the query across a number of resources to generate a result;

the processor further configured to execute a canonical model manager having a number of models used to identify relationships between types of information within the number of resources and the query; and

the processor further configured to execute a context manager configured to manage the context of the query and the relationships identified by the canonical model manager, to position the number of resources for access by the knowledge manager.

2. The system of claim 1, wherein the query is at least one of a natural language query and a logical form query.

3. The system of claim 2, wherein the knowledge manager is further configured to convert the natural language query into logical form.

4. The system of claim 1, further comprising:

an information queuing manager, executed by the processor, configured to spawn a number of agents to monitor the number of resources and position information within the number of resources.

5. The system of claim 4, wherein the number of agents further comprises:

a first number of resource monitoring agents configured to track contextually relevant information within the number of resources; and

a second number of positioning agents configured to extract and position information within the network.

6. The system of claim 1, wherein the knowledge manager further comprises:

a natural language interface configured to parse the natural language query to identify a number of words and a number of phrases, wherein the natural language interface uses the number of words and the number of phrases to map the natural language query to a number of domain models.

7. The system of claim 1, wherein the knowledge manager further comprises:

an image data view controller configured to integrate the result with a number of views for display over a user interface.

8. The system of claim 7, wherein the image data view controller further includes providing the querent access to at least one of a temporal view, geospatial view, topic map, concept map, radial spanning tree, tree map, and a node connection diagram over the user interface.

9. The system of claim 1, wherein the knowledge manager is configured to process the query across the number of resources to generate the result, and wherein the result is a first result, the system further comprising:

a result filter generating a filtered result from the first result, wherein the result filter uses the context manager to sort information in logical result according to the context of the query from the querent, and generates the filtered result.

10. A method for positioning data within a network, the method comprising:

receiving a query from a querent, wherein the query is a natural language query from the querent received over a user interface;

determining, on a processor, whether the query is a session command;

responsive to a determination that the query is a session command, determining whether the querent ends a session;

responsive to a determination that the querent ends the session, updating all caches, marking all waypoints, generating reports, and clearing contexts;

responsive to a determination that the query is not a session command, determining, using a processor, whether the query is in logical form;

responsive to a determination that the query is in logical form, comparing entries of the logical form query with canonical models passed from a semantic query engine;

determining, using the processor, whether the entries of the logical form query match entries of the canonical models;

responsive to a determination that the entries of the logical form query match the entries of the canonical models, passing a relational form query to a knowledge manager;

responsive to a determination that the query is not a session command, parsing, on the processor, the natural language query to identify a number of words and a number of phrases;

mapping, on the processor, the natural language query to a number of domain models using the number of words and the number of phrases;

converting, on the processor, the natural language query into a logical query using the number of domain models mapped to the natural language query;

identifying, on the processor, relationships between types of information within a number of resources and the natural language query; and

processing the logical query across the number of resources to generate a result, the result returnable to the querent via the user interface providing the querent access to an integrated data view controller.

11. The method of claim 10 further comprising:

tracking a history of natural language queries using a number of waypoints, wherein the number of waypoints provides a context path for the history of natural language queries.

12. The method of claim 10 further comprising:

monitoring availability of information within the number of resources.

13. The method of claim 10, wherein providing the querent access to the integrated data view controller further includes providing the querent access to at least one of a temporal view, geospatial view, topic map, concept map, radial spanning tree, tree map, and a node connection diagram.

14. The method of claim 10 further comprising:

searching the cache for existing duplicate queries; and

responsive to finding a duplicate query, retrieving cached results and running the query again.

15. A method for knowledge management, the method comprising:

receiving a query from a querent;

determining, on a processor, whether the query is a session command;

responsive to a determination that the query is a session command, determining whether the querent ends a session;

responsive to a determination that the querent ends the session, updating all caches, marking all waypoints, generating reports, and clearing contexts;

responsive to a determination that the query is not a session command, determining, using the processor, whether the query is in logical form;

responsive to a determination that the query is in logical form, comparing entries of the logical form query with canonical models passed from a semantic query engine;

determining, using the processor, whether the entries of the logical form query match entries of the canonical models; and

responsive to a determination that the entries of the logical form query match the entries of the canonical models, passing a relational form query to a knowledge manager.

16. The method of claim 15 further comprising:

responsive to a determination that the query is not in logical form, parsing the query into logical form before comparing entries of the logical form query with the entries of the canonical models passed from the semantic query engine.

17. The method of claim 15 further comprising:

responsive to a determination that the entries do not match, requesting necessary information to answer the query from the querent;

determining whether the querent revises the query;

responsive to a determination that the querent revises the query, parsing free-form text input; and

parsing the free-form text input into logical form.

18. The method of claim 15 further comprising:

searching the cache for existing duplicate queries; and

responsive to finding no duplicate query, processing the logical form query against available data in a number of resources.

19. The method of claim 15 further comprising:

transmitting a response of the query to the querent and updating the cache.