Optimized Data Visualization According to Natural Language Query

• US 20150100588A1
• Filed: 10/09/2013
• Published: 04/09/2015
• Est. Priority Date: 10/09/2013
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Allen, Corville O., Freed, Andrew Ronald
• Granted Patent: US 10,572,473 B2
• Time in Patent Office: Days
• US Class Current: 707/748
• CPC Class Codes: G06F 16/243 Natural language query formulation

Abstract

An optimal visualization format for a data corpus is automatically selected and generated based upon a natural language query or statement about the data corpus from a user by accessing the subject data corpus; receiving the query or statement from the user a natural language expression; identifying symbols in the query or statement through natural language processing; mapping the symbols to weights for a plurality of visualization formats; scoring the visualization formats; and generating a visualization of the subject data corpus according to the scores. Optional metadata, such as row and column labels, database field labels, and XML DTD'"'"'s may be mined for symbols, as well. The new tool may generate the visualization as a digital image file, a digital document file, a digital movie file, a digital three-dimensional model file, or a combination of these.

Claims

1. A method for selecting an optimal visualization format of a data corpus according to a natural language query about the data corpus comprising:

accessing by a computer a subject data corpus;

receiving by a computer a query or statement from a user comprising a natural language expression;

identifying by a computer one or more symbols in the query or statement through natural language processing;

mapping the symbols to one or more weights for a plurality of visualization formats;

scoring by a computer the visualization formats using the weights and a scoring calculation; and

generating by a computer a visualization of the subject data corpus according to the visualization format scores.

2. The method as set forth in claim 1 further comprising accessing by a computer metadata associated with the data corpus, and wherein the identifying of symbols further comprises applying natural language processing to the metadata.

3. The method as set forth in claim 2 wherein the metadata comprises row and column labels.

4. The method as set forth in claim 2 wherein the metadata comprises field labels from database records.

5. The method as set forth in claim 2 wherein the metadata comprises an extensible markup language document type description.

6. The method as set forth in claim 1 wherein the scoring calculation comprises summing by the computer of weight values for each visualization format.

7. The method as set forth in claim 1 wherein the scoring calculation comprises averaging by the computer of weight values for each visualization format.

8. The method as set forth in claim 1 wherein the generating of a visualization comprises generating a digital image file.

9. The method as set forth in claim 1 wherein the generating of a visualization comprises generating a digital document file.

10. The method as set forth in claim 1 wherein the generating of a visualization comprises generating a digital movie file.

11. The method as set forth in claim 1 wherein the generating of a visualization comprises generating a digital three-dimensional model file.

12. A computer program product for selecting an optimal visualization format of a data corpus according to a natural language query about the data corpus comprising:

one or more computer readable data storage devices; and

program instructions stored by the data storage device for causing a processor to;

access a subject data corpus;

receive a query or statement from a user comprising a natural language expression;

identify one or more symbols in the query or statement through natural language processing;

map the symbols to one or more weights for a plurality of visualization formats;

score the visualization formats using the weights and a scoring calculation; and

generate a visualization of the subject data corpus according to the visualization format scores.

13. The computer program product as set forth in claim 12 wherein the program instructions further comprise instructions to access metadata associated with the data corpus, and wherein the identifying of symbols further comprises applying natural language processing to the metadata.

14. The computer program product as set forth in claim 13 wherein the metadata comprises one or more metadata types selected from the group consisting of row and column labels, field labels from database records, and an extensible markup language document type description.

15. The computer program product as set forth in claim 13 wherein the scoring calculation comprises a calculation selected from the group consisting of summing by the computer of weight values for each visualization format, and averaging by the computer of weight values for each visualization format.

16. The computer program product as set forth in claim 13 wherein the generating of a visualization comprises generating a visualization selected from the group consisting of a digital image file, a digital document file, a digital movie file, and a digital three-dimensional model file.

18. The system as set forth in claim 12 wherein the program instructions further comprise instructions to access metadata associated with the data corpus, and wherein the identifying of symbols further comprises applying natural language processing to the metadata.

19. The system as set forth in claim 18 wherein the metadata comprises one or more metadata types selected from the group consisting of row and column labels, field labels from database records, and an extensible markup language document type description.

20. The system as set forth in claim 13 wherein the scoring calculation comprises a calculation selected from the group consisting of summing by the computer of weight values for each visualization format, and averaging by the computer of weight values for each visualization format, and wherein the generating of a visualization comprises generating a visualization selected from the group consisting of a digital image file, a digital document file, a digital movie file, and a digital three-dimensional model file.

17. A system for selecting an optimal visualization format of a data corpus according to a natural language query about the data corpus comprising:

a processor for executing program instructions; and

one or more computer readable data storage devices storing program instructions for causing a processor to;

access a subject data corpus;

receive a query or statement from a user comprising a natural language expression;

identify one or more symbols in the query or statement through natural language processing;

map the symbols to one or more weights for a plurality of visualization formats;

score the visualization formats using the weights and a scoring calculation; and

generate a visualization of the subject data corpus according to the visualization format scores.