AUTOMATED GENERATION OF ANALYTIC AND VISUAL BEHAVIOR

• US 20120158754A1
• Filed: 12/17/2010
• Published: 06/21/2012
• Est. Priority Date: 12/17/2010
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Mital, Vijay, Uritsky, Max, Poozhiyil, Suraj, Khosravy, Moe
• Granted Patent: US 9,171,272 B2
• Time in Patent Office: Days
• US Class Current: 707/754
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

A data marketplace infrastructure allows a data source company or a third party to automate generation of one or more applications in association a data feed. In contrast to custom, manual development of applications, the data marketplace infrastructure constructs applications that suggest applicability to the data feed. Factors suggesting applicability include without limitation similarity of data structures and similarity of subject matter. Based on an applicability determination, patterns of historical visual usage and patterns of historical business logic usage may be used to identify expressions specifying the visuals and business logic that may be copied to and used in a new application in association with the data feed. Furthermore, previewers can provide feedback to help tune which automatically generated applications are maintained in association with the data feed and which are discarded or altered in some way.

Claims

1. A method comprising:

extracting expressions from one or more existing applications associated with a first data feed, wherein the extracted expressions satisfy an applicability criterion relative to a second data feed;

generating one or more new applications to evaluate data from the second data feed, wherein the one or more new applications include the extracted expressions; and

adjusting availability of individual ones of the new applications based on feedback received from usage of the one or more of the new applications in association with the second data feed.

2. The method of claim 1 wherein the applicability criterion includes a similarity measure of subject matter in the first data feed and subject matter in the second data feed.

3. The method of claim 1 wherein the applicability criterion includes a similarity measure of data structure in the first data feed and data structure in the second data feed.

4. The method of claim 1 wherein the extracted expressions are identified based on their specification of a visual entity from one of the existing applications.

5. The method of claim 1 wherein the extracted expressions are identified based on their specification of a business logic entity from one of the existing applications.

6. The method of claim 1 wherein the adjusting operation comprises:

maintaining a new application as available to clients for download and use, if the feedback is positive.

7. The method of claim 1 wherein the adjusting operation comprises:

deleting the new application from generated application options available to clients for download and use, if the feedback is negative.

8. The method of claim 1 wherein the adjusting operation comprises:

identifying the new application for manual adjustment, if the feedback is negative.

9. One or more computer-readable storage media encoding computer-executable instructions for executing on a computer system a computer process, the computer process comprising:

extracting expressions from one or more existing applications associated with a first data feed, wherein the extracted expressions satisfy an applicability criterion relative to a second data feed;

generating one or more new applications to evaluate data from the second data feed, wherein the one or more new applications include the extracted expressions; and

adjusting availability of individual ones of the new applications based on feedback received from usage of the one or more of the new applications in association with the second data feed.

10. The one or more computer-readable storage media of claim 9 wherein the applicability criterion includes a similarity measure of subject matter in the first data feed and subject matter in the second data feed.

11. The one or more computer-readable storage media of claim 9 wherein the applicability criterion includes a similarity measure of data structure in the first data feed and data structure in the second data feed.

12. The one or more computer-readable storage media of claim 9 wherein the extracted expressions are identified based on their specification of a visual entity from one of the existing applications.

13. The one or more computer-readable storage media of claim 9 wherein the extracted expressions are identified based on their specification of a business logic entity from one of the existing applications.

14. The one or more computer-readable storage media of claim 9 wherein the adjusting operation comprises:

maintaining a new application as available to clients for download and use, if the feedback is positive.

15. The one or more computer-readable storage media of claim 9 wherein the adjusting operation comprises:

deleting the new application from generated application options available to clients for download and use, if the feedback is negative.

16. The one or more computer-readable storage media of claim 9 wherein the adjusting operation comprises:

identifying the new application for manual adjustment, if the feedback is negative.

17. A system comprising:

an autogenerator engine that extracts expressions from one or more existing applications associated with a first data feed, wherein the extracted expressions satisfy an applicability criterion relative to a second data feed, and generates one or more new applications to evaluate data from the second data feed, wherein the one or more new applications include the extracted expressions; and

a feedback manager that adjusts availability of individual ones of the new applications based on feedback received from usage of the one or more of the new applications in association with the second data feed.

18. The system of claim 17 wherein the applicability criterion includes a similarity measure of subject matter in the first data feed and subject matter in the second data feed.

19. The system of claim 17 wherein the applicability criterion includes a similarity measure of data structure in the first data feed and data structure in the second data feed.

20. The system of claim 17 wherein the extracted expressions are identified based on their specification of at least one of a visual entity or a business logic entity from one of the existing applications.