DETERMINATION OF ROOT CAUSE(S) OF SYMPTOMS USING STOCHASTIC GRADIENT DESCENT

• US 20090024356A1
• Filed: 07/16/2007
• Published: 01/22/2009
• Est. Priority Date: 07/16/2007
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Kiciman, Erme Mehment, Platt, John C.
• Application Number:
  US11/778,421
• Publication Number:
  US 20090024356A1
• Time in Patent Office: Days
• US Class Current: 702/181
• CPC Class Codes: G05B 23/0281 Quantitative, e.g. mathematical distance; Clustering; Neural networks; Statistical analysis
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Diagnosis of one or more root causes of symptoms is performed by using stochastic gradient descent to find the optimal parameters of a variational distribution. This methodology, called variational gradient descent, permits fast diagnosis for a large number (greater than 1,000) or very large number (greater than 1,000,000) of symptom observations. A real-time application of the root cause diagnosis can determine currently occurring intermittent root causes. Diagnosis can be performed in a number of scenarios, such as medical disease detection or computer/network failure.

Claims

1. A method for determining root causes, comprising:

for each of multiple symptom observations,

receiving an indication of a symptom observation; and

adjusting a probability of each root cause that can give rise to the observed symptom; and

indicating one or more root causes of the observed symptoms.

2. The method of claim 1 wherein the indicating of one or more root causes of the symptoms includes:

for each of at least some symptom observations,

indicating a current probability of each root cause that can give rise to the observed symptom.

3. The method of claim 1 wherein for at least one symptom the receiving of the indication of a symptom observation includes receiving an indication of a substantially real-time symptom observation.

4. The method of claim 1 wherein the number of multiple symptom observations exceeds five thousand.

5. The method of claim 1 wherein the symptoms are medical symptoms.

6. The method of claim 1 wherein the symptoms are network observations and the root causes are a plurality of software or hardware faults.

7. The method of claim 1 wherein the indicating of one or more root causes of the observed symptoms includes indicating two or more root causes of the observed symptoms.

8. The method of claim 1 wherein the indicating of one or more root causes of the observed symptoms includes selectively indicating to a user one or more root causes based on predetermined rules.

9. The method of claim 1 wherein the adjusting of a probability of each root cause that can give rise to the observed symptom increases similarity between an estimated root cause and a true root cause of the observed symptom.

10. A root cause determination system comprising:

a symptom acquiring component that receives indications of multiple symptom observations; and

a root cause determination component that determines one or more root causes from the symptoms using variational gradient descent.

11. The system of claim 10 wherein the symptom acquiring component receives substantially real-time indications of symptom observations and the root cause determination component determines a current root cause in substantially real-time.

12. The system of claim 10 wherein the one or more root causes are at least one of medical diseases, faults of a computer system, and faults of a computer network.

13. The system of claim 10, further comprising an alert component that indicates at least one of the determined one or more root causes to a technician user.

14. The system of claim 10, further comprising a prioritization component that determines how to indicate at least one of the determined one or more root causes to a technician user.

15. The system of claim 14 wherein the prioritization component comprises an artificial intelligence component.

16. The system of claim 10 wherein the root cause determination component performs gradient descent in order to accomplish variational inference.

17. The system of claim 10 wherein the root cause determination component performs variational gradient descent without a calibration set.

18. A diagnostic tool comprising:

means for receiving an indication of multiple symptom observations; and

means for determining one or more diseases underlying the symptoms using variational gradient descent.

19. The diagnostic tool of claim 18 wherein the multiple symptoms exceed five thousand positive symptoms.

20. The diagnostic tool of claim 18 wherein the means for determining one or more diseases underlying the symptoms using variational gradient descent determines a substantially real-time estimate of disease probabilities.