Expertise-Responsive Adaptive Workflow System and Method

• US 20120035976A1
• Filed: 10/20/2011
• Published: 02/09/2012
• Est. Priority Date: 05/20/2004
• Status: Abandoned Application

• Current Assignee: Manyworlds Incorporated
• Original Assignee: Manyworlds Incorporated
• Inventors: Flinn, Steven Dennis, Moneypenny, Naomi Felina
• Application Number:
  US13/277,994
• Publication Number:
  US 20120035976A1
• Time in Patent Office: Days
• US Class Current: 705/7.27
• CPC Class Codes: G06F 16/60 of audio data
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/0633 Workflow analysis
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

A computer-implemented system and method for expertise-responsive adaptive workflow delivers workflow step recommendations based, at least in part, on inferences from behavioral information and a level of expertise. Experts may be designated manually or automatically, and may inform the generation of the recommendations. The degree to which behavioral information of designated experts influences recommendations may be tuned by recommendation recipients. Variations of the system and method include generating the recommendations in accordance with physiological responses and/or monitored physical locations. Information as to why recommendations were delivered to recommendation recipients may be provided to the recommendation recipients.

Claims

1. A method, comprising:

contributing a plurality of usage behaviors to a computer-implemented usage function while interacting with a computer-implemented function executed on a processor-based device that comprises a representation of process workflow, wherein the representation of process workflow comprises a plurality of workflow steps; and

receiving a recommendation comprising a workflow step that is selected from the plurality of workflow steps, wherein the recommendation is generated by a computer-implemented function based, at least in part, on an inference from the plurality of usage behaviors and an expertise level.

2. The method of claim 1, further comprising:

contributing the plurality of usage behaviors, wherein one behavior of the plurality of behaviors is a physiological response.

3. The method of claim 1, further comprising:

interacting with the computer-implemented function executed on a processor-based device that comprises a representation of process workflow, wherein the interaction comprises a performance of a workflow step.

4. The method of claim 1, further comprising:

receiving the recommendation comprising the workflow step, wherein the recommendation is generated in accordance with a designation of a user as an expert.

5. The method of claim 4, further comprising:

receiving the recommendation comprising the workflow step, wherein the recommendation is generated in accordance with the designation of a user as an expert, wherein the designation is automatically determined.

6. The method of claim 1, further comprising:

receiving the recommendation comprising the workflow step, wherein the recommendation is generated in accordance with an expertise tuning control.

7. The method of claim 1, further comprising:

receiving the recommendation, wherein the recommendation comprises a plurality of sequenced workflow steps selected from the plurality of workflow steps.

8. The method of claim 1, further comprising:

receiving an explanation comprising a reason as to why the recommendation was delivered to the recommendation recipient.

9. A computer-implemented system, comprising:

a computer-implemented workflow function comprising a plurality of workflow steps;

a computer-implemented usage function that accesses a plurality of usage behaviors associated with the workflow function; and

a recommendation-generating function executed on a processor-based device that generates a recommendation comprising a workflow step that is selected from the plurality of workflow steps, wherein the recommendation is generated based, at least in part, on an inference from the plurality of usage behaviors and an expertise level.

10. The system of claim 9, further comprising:

the plurality of usage behaviors, wherein at least one of the plurality of usage behaviors is a physiological response.

11. The system of claim 9, further comprising:

the plurality of usage behaviors, wherein at least one of the plurality of usage behaviors is a monitored location.

12. The system of claim 9, further comprising:

the recommendation-generating function that generates the recommendation, wherein the recommendation is generated in accordance with a designation of a user as an expert.

13. The system of claim 12, further comprising:

the recommendation-generating function that generates the recommendation, wherein the recommendation is generated in accordance with the designation of a user as an expert, wherein the designation is automatically determined.

14. The system of claim 9, further comprising:

the recommendation-generating function that generates the recommendation, wherein the recommendation is generated in accordance with an expertise tuning control.

15. The system of claim 9, further comprising:

the recommendation-generating function that generates the recommendation, wherein the recommendation comprises a plurality of sequenced workflow steps selected from the plurality of workflow steps.

16. The system of claim 9, further comprising:

an explanatory function that delivers an explanation to the recommendation recipient comprising a reason as to why the recommendation was delivered to the recommendation recipient.

17. A computer-implemented system, comprising:

a computer-implemented workflow function comprising a plurality of workflow steps;

a computer-implemented usage function that accesses a plurality of usage behaviors associated with the workflow function;

a recommendation-generating function executed on a processor-based device that generates a recommendation for delivery to a recommendation recipient comprising a workflow step that is selected from the plurality of workflow steps, wherein the recommendation is generated based, at least in part, on an inference from the plurality of usage behaviors; and

a computer-implemented explanatory function that delivers logic to the recommendation recipient as to why the recommendation was delivered to the recommendation recipient.

18. The system of claim 17, further comprising

the recommendation-generating function, wherein the recommendation-generating function generates the recommendation in accordance with a designation of a user as an expert.

19. The system of claim 17, further comprising

the recommendation-generating function, wherein the recommendation-generating function generates the recommendation in accordance with an experience level.

20. The system of claim 17, further comprising

the recommendation-generating function, wherein the recommendation-generating function generates the recommendation in accordance with an expertise tuning control.