Visualization engine for a knowledge management system

• US 9,720,984 B2
• Filed: 10/22/2012
• Issued: 08/01/2017
• Est. Priority Date: 10/22/2012
• Status: Active Grant

• Current Assignee: Bank of America Corp.
• Original Assignee: Bank of America Corp.
• Inventors: McClung, Susan, Hofmeister, Michael K.
• Primary Examiner(s): Uddin, Md. I
• Application Number:
  US13/657,111
• Publication Number:
  US 20140114953A1
• Time in Patent Office: 1,744 Days
• Field of Search: 707722, 707723, 707780, 707E17082
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 16/904 Browsing; Visualisation therefor for navigating the web G06F16/954; browsing optimisation for the web G06F16/957

Abstract

A system includes a memory operable to store visualization rules. The system also includes a processor communicatively coupled to the memory. The processor is operable to receive a visualization request relating to information stored in an ontology. The processor is further operable to parse the visualization request to generate a search query. The processor is further operable to submit the search query to the ontology. The processor is further operable to receive, in response to the query, a result. The result includes a plurality of instances and a plurality of relationships between the instances. The processor is further operable to generate a visual representation of the result using the visualization rules.

Claims

1. A system, comprising:

a memory operable to store visualization rules, the visualization rules comprising level of detail rules, reduction rules, and rewriting rules; and

a processor communicatively coupled to the memory and operable to;

receive a visualization request relating to information stored in an ontology;

parse the visualization request to generate a search query;

submit the search query to the ontology, wherein the ontology is dynamically created to store retrieved data that is collected from a data source;

perform data mitigation to process the retrieved data to detect and resolve conflicts among classified tokens provided by data agent, wherein the data mitigation uses quality score, trust score, and rate of decay for the data source;

receive, in response to the query, a result comprising a plurality of instances associated with the classified tokens and a plurality of relationships between the instances; and

generate a visual representation of the result using the visualization rules, wherein generating the visual representation of the result using the visualization rules comprises;

identifying a relationship between a first instance and a second instance from the plurality of instances within the result;

removing the relationship between the first instance and the second instance from the results; and

removing the first instance from the results when the first instance has no relationships with any other instances from the plurality of instances.

2. The system of claim 1, wherein parsing the visualization request to generate the search query comprises reducing the scope of the search query based on the visualization rules.

3. The system of claim 1, wherein generating the visual representation of the result using the visualization rules comprises selecting an instance from the plurality of instances for removal based on the visualization rules.

4. The system of claim 1, wherein generating the visual representation of the result using the visualization rules comprises selecting a third instance and a fourth instance from the plurality of instances to be combined into a consolidated instance based on the visualization rules.

5. The system of claim 1, wherein the visualization rules control a level of detail presented in the visual representation.

6. The system of claim 5 wherein the visualization rules are applied iteratively until the level of detail meets a selected threshold.

7. The system of claim 5, wherein the level of detail is adaptively determined based on the search results.

8. The system of claim 7 wherein the determined level of detail is based at least in part on an average number of relationships connected to the plurality of instances in the search results.

9. A method, comprising:

receiving, by a processor, a visualization request relating to information stored in an ontology;

parsing, by the processor, the visualization request to generate a search query;

submitting, by the processor, the search query to the ontology, wherein the ontology is dynamically created to store retrieved data that is collected from a data source;

perform data mitigation to process the retrieved data to detect and resolve conflicts among classified tokens provided by data agent, wherein the data mitigation uses quality score, trust score, and rate of decay for the data source;

receiving, by the processor, in response to the query, a result comprising a plurality of instances associated with the classified tokens and a plurality of relationships between the instances; and

generating, by the processor, a visual representation of the result using visualization rules stored in a memory, the visualization rules comprising level of detail rules, reduction rules, and rewriting rules, wherein generating the visual representation of the result using the visualization rules comprises;

identifying a relationship between a first instance and a second instance from the plurality of instances within the results;

removing the relationship between the first instance and the second instance from the results; and

removing the first instance from the results when the first instance has no relationships with any other instances from the plurality of instances.

10. The method of claim 9, wherein parsing the visualization request to generate the search query comprises reducing the scope of the search query based on the visualization rules.

11. The method of claim 9, wherein generating the visual representation of the result using the visualization rules comprises selecting an instance from the plurality of instances for removal based on the visualization rules.

12. The method of claim 9, wherein generating the visual representation of the result using the visualization rules comprises selecting a third instance and a fourth instance from the plurality of instances to be combined into a consolidated instance based on the visualization rules.

13. The method of claim 9, wherein the visualization rules control a level of detail presented in the visual representation.

14. The method of claim 13, wherein the level of detail is adaptively determined based on the search results.

15. One or more non-transitory computer readable storage media embodying logic that is operable when executed by one or more processors to:

receive a visualization request relating to information stored in an ontology;

parse the visualization request to generate a search query;

submit the search query to the ontology, wherein the ontology is dynamically created to store retrieved data that is collected from a data source;

perform data mitigation to process the retrieved data to detect and resolve conflicts among classified tokens provided by data agent, wherein the data mitigation uses quality score, trust score, and rate of decay for the data source;

receive, in response to the query, a result comprising a plurality of instances associated with the classified tokens and a plurality of relationships between the instances; and

generate a visual representation of the result using visualization rules stored in a memory, the visualization rules comprising level of detail rules, reduction rules, and rewriting rules, wherein generating the visual representation of the result using the visualization rules comprises;

identifying a relationship between a first instance and a second instance from the plurality of instances within the result;

removing the relationship between the first instance and the second instance from the results; and

removing the first instance from the results when the first instance has no relationships with any other instances from the plurality of instances.

16. The storage media of claim 15, wherein parsing the visualization request to generate the search query comprises reducing the scope of the search query based on the visualization rules.

17. The storage media of claim 15, wherein generating the visual representation of the result using the visualization rules comprises selecting an instance from the plurality of instances for removal based on the visualization rules.

18. The storage media of claim 15, wherein generating the visual representation of the result using the visualization rules comprises selecting a third instance and a fourth instance from the plurality of instances to be combined into a consolidated instance based on the visualization rules.

19. The storage media of claim 15, wherein the visualization rules control a level of detail presented in the visual representation.

20. The storage media of claim 19, wherein the level of detail is adaptively determined based on the search results.