CANDIDATE VISUALIZATION TECHNIQUES FOR USE WITH GENETIC ALGORITHMS

• US 20170213135A1
• Filed: 04/06/2017
• Published: 07/27/2017
• Est. Priority Date: 09/23/2015
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Rope, Daniel J., Keahey, T. Alan, Wills, Graham J.
• Granted Patent: US 10,599,979 B2
• Time in Patent Office: Days
• CPC Class Codes: G06N 3/126 Evolutionary algorithms, e.g. genetic algorithms or genetic programming
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs

Abstract

According to one embodiment, a method for generating a plurality of candidate visualizations. The method may include receiving a scenario description. The method may also include collecting a plurality of expert data using a training system based on the received scenario description. The method may further include generating at least one predictive model based on the collected plurality of expert data in order to execute the at least one generated predictive model during an application of a plurality of genetic algorithms.

Claims

1. A computer system for generating a plurality of candidate visualizations, the computer system comprising:

one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising;

receiving a scenario description;

collecting a plurality of expert data using a training system based on the received scenario description; and

generating at least one predictive model based on the collected plurality of expert data in order to execute the at least one generated predictive model during an application of a plurality of genetic algorithms.

2. The computer system of claim 1, wherein the plurality of expert data includes at least one of a plurality of action data, a plurality of metric data, and a plurality of opinion data.

3. The computer system of claim 1, wherein the training system collects the plurality of expert data through at least one of an expert selecting a preferred visualization within a plurality of candidate visualizations and an expert submitting an opinion related to the preferred visualization.

4. The computer system of claim 1, wherein the training system includes at least one of a central data storage facility, a plurality of web-based deployment capabilities, and scalability to a corresponding number of experts using the training system.

5. The computer system of claim 1, further comprising:

updating the training system based on the at least one generated predictive model.

6. The computer system of claim 1, wherein generating the at least one predictive model may include using at least one of a plurality of boosted decision trees, text categorization, and neural networking.

7. The computer system of claim 1, wherein each at least one generated predictive model may be used to derive an overall fitness evaluation score to rate a candidate visualization when executing the plurality of genetic algorithms.

8. A computer program product for generating a plurality of candidate visualizations, the computer program product comprising:

one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor, the program instructions comprising;

program instructions to receive a scenario description;

program instructions to collect a plurality of expert data using a training system based on the received scenario description; and

program instructions to generate at least one predictive model based on the collected plurality of expert data in order to execute the at least one generated predictive model during an application of a plurality of genetic algorithms.

9. The computer program product of claim 8, wherein the plurality of expert data includes at least one of a plurality of action data, a plurality of metric data, and a plurality of opinion data.

10. The computer program product of claim 8, wherein the training system collects the plurality of expert data through at least one of an expert selecting a preferred visualization within a plurality of candidate visualizations and an expert submitting an opinion related to the preferred visualization.

11. The computer program product of claim 8, wherein the training system includes at least one of a central data storage facility, a plurality of web-based deployment capabilities, and scalability to a corresponding number of experts using the training system.

12. The computer program product of claim 8, further comprising:

program instructions to update the training system based on the at least one generated predictive model.

13. The computer program product of claim 8, wherein generating the at least one predictive model may include using at least one of a plurality of boosted decision trees, text categorization, and neural networking.