PREDICTION SYSTEM BASED ON WEIGHTED EXPERT OPINIONS USING PRIOR SUCCESS MEASURES

• US 20040133393A1
• Filed: 01/04/2004
• Published: 07/08/2004
• Est. Priority Date: 01/04/2003
• Status: Abandoned Application

• Current Assignee: Enovus
• Original Assignee: Enovus
• Inventors: MISIUM, GEORGE
• Application Number:
  US10/707,680
• Publication Number:
  US 20040133393A1
• Time in Patent Office: Days
• US Class Current: 702/181
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

This invention is a prediction and reward system and method based on pooling the opinions of experts by using quantitative measures of prior prediction performance to weigh the opinions. This invention enables a computer-network based system capable of generating predictions based on expert opinions as well as measures of expert performance.

Claims

1. A system for predicting the outcome of an event comprising:

input/output means;

memory means;

processing means;

means for experts to enter their opinions on said event outcome into said input/output means;

means for capturing the data from said input/output means;

means for storing measures of prior performance by different experts in said memory means;

means for calculating a prediction for the outcome of said event based on the average of said expert opinions weighted by said measures of prior performance; and

means for storing in said memory means and for transmitting to said input/output means the prediction calculated by said processing means;

2. A system according to claim 1, wherein said expert opinions are prompted by said input/output means by asking questions from said experts.

3. A system according to claim 1, wherein said processing means compares the actual outcome of the event to the individual expert opinions, recalculates the expert performance weight, and transmits the recalculated weight to said memory means to be used as new measure of expert prior performance.

4. A system according to claim 1, wherein said input/output means receives external inquiries on prior expert performance and, upon validation by said processing means, issues measures of prior expert performance.

5. A system according to claim 4, wherein said measures of prior expert performance are recalculated by said processing means into participatory rewards or penalties.

6. A system according to claim 1, wherein said input/output means, memory means, and processing means are part of a computer environment internal to an organization or connected to the Internet.

7. A system according to claim 1, wherein said input/output means is a website displaying specific questions, validating the identity and capturing the opinion of an expert, and issuing measures and rewards based on expert performance.

8. A method for issuing predictions on the outcome of an event comprising the steps of:

eliciting and receiving expert opinions;

storing said expert opinions;

weighing said expert opinions by measures of expert prior performance;

pooling the weighted opinions; and

issuing a prediction resulting from the pooling of weighted opinions.

9. A method according to claim 8 wherein:

said measures of expert performance are updated by comparing the expert predictions to the actual outcome of the event.

10. A method according to claim 8 wherein:

said experts are human beings of varying degrees of skill and expertise.

11. A method according to claim 8 wherein:

said experts are devices capable of putting forward an answer or opinion.

12. A method according to claim 11 wherein:

said devices are classifiers used for speech or pattern recognition.

13. A method according to claim 8 wherein:

said pooling of weighted opinions is a mathematical average.

14. A method according to claim 8 wherein:

said pooling of weighted opinions is an arithmetic average with individual weights assigned to expert opinions normalized by the same factor to make the sum of all weight equals to 1.

15. A method according to claim 8 wherein:

said measure of prior expert performance is a mathematical function monotonously decreasing with the amount of deviation between expert opinion and outcome.

16. A method according to claim 8 wherein:

said measure of prior expert performance is an average of inverse exponentials of absolute differences between prior expert opinion and actual event outcome.

17. A method according to claim 16 wherein:

said average of inverse exponentials is a summation of inverse exponentials arithmetically factored by their time-series position in the sequence of previous opinions.

18. A method according to claim 8 wherein:

said measure of prior performance by the expert is first evaluated based on a test using historical data.

19. A method according to claim 8 wherein:

said measure of prior performance is based on a mapping of prior prediction capabilities in a different realm of activity.

20. A method according to claim 8 wherein:

said weighing of prior performance of experts is realized utilizing operational analysis techniques or neural networks.

21. A method according to claim 8 further comprising:

issuing a measure of an expert'"'"'s prior performance upon validating a request for performance measure.

22. A method according to claim 8 further comprising:

calculating an expert'"'"'s reward or penalty based on said measure of an expert'"'"'s prior performance.