Modeless user interface incorporating automatic updates for developing and using Bayesian belief networks

• US 7,536,372 B2
• Filed: 07/18/2005
• Issued: 05/19/2009
• Est. Priority Date: 07/26/2004
• Status: Active Grant

• Current Assignee: Charles River Analytics, Inc.
• Original Assignee: Charles River Analytics, Inc.
• Inventors: Pfautz, Jonathan D., Cox, Zachary T.
• Primary Examiner(s): Holmes; Michael B
• Application Number:
  US11/183,397
• Publication Number:
  US 20060020568A1
• Time in Patent Office: 1,401 Days
• Field of Search: 706/52
• US Class Current: 706/52
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks

Abstract

An application for developing and using a model of a Bayesian Network to compute beliefs. The application provides an interface through which a user may specify the construction of the Bayseian Network, such as by specifying nodes in the network, parameters associated with the nodes, conditional probability distributions associated with the parameters or evidence that a parameter has a particular value. The application builds an inference engine based on user input specifying the construction of the Bayesian Network and uses it to compute beliefs. The application provides a user interface through which a user may specify the construction of the Bayesian Network and automatically updates an output reflecting beliefs. The input and output information may be available to the user simultaneously without switching operating modes of the application.

Claims

1. A data analysis and modeling system, comprising:

a processing system configured to;

a) receive a plurality of inputs representing evidence and information indicative of a structure of a belief network;

b) provide at least one output representative of at least one belief based on the plurality of inputs; and

c) automatically update the at least one output representative of at least one belief in response to at least one of the plurality of inputs having a value representative of a change to the evidence or the information indicative of the structure of the belief network.

2. The data analysis and modeling system of claim 1, wherein the processing system is further configured to model the belief network as a plurality of interconnected nodes and wherein the information indicative of a structure comprises information indicative of interconnections between the nodes and at least one conditional probability distribution associated with a node.

3. The data analysis and modeling system of claim 2, wherein the processing system is further configured to automatically update in response to an input representative of a change in the at least one conditional probability distribution.

4. The data analysis and modeling system of claim 2, wherein the processing system is further configured to automatically update in response to one of the plurality of inputs representing a change in the evidence.

5. The data analysis and modeling system of claim 1, wherein the processing system is further configured to:

selectively place, prior to automatically updating the output, the belief network development application in an operating state in which the outputs are automatically updated in response to an input representative of a change to the evidence or the information indicative of the structure of the belief network.

6. The data analysis and modeling system of claim 1, wherein the processing system is further configured to automatically update the output representative of at least one belief in response to one of the plurality of inputs representing a change within only a predetermined subset of inputs.

7. The data analysis and modeling system of claim 6, wherein the processing system is further configured to automatically update the output representative of at least one belief in response to one of the plurality of inputs representing a change in evidence or a change in a conditional probability distribution.

8. The data analysis and modeling system of claim 6, wherein the processing system is further configured to:

receive an input from a human user representative of the predetermined subset of inputs.

9. The data analysis and modeling system of claim 1, wherein further comprising a data generating subsystem coupled to the processing system, and wherein the processing system is further configured to:

receive one of the plurality of inputs having a value representative of a change from the data generating subsystem.

10. A computer-readable medium having stored therein computer-readable instructions for a processor, wherein said instructions when executed by said processor cause said processor to:

receive information representative of a Bayesian network

detect received information representative of a modification of the Bayesian network; and

build an inference engine for computing beliefs based on the Bayesian network in response to the detected modification of the Bayesian network.

11. The computer-readable medium of claim 10, wherein the Bayesian network is modeled as a plurality of interconnected nodes, and wherein the instructions further cause information to be detected that represents a change to the model of the interconnected nodes.

12. The computer-readable medium of claim 10, wherein the Bayesian network is modeled as a plurality of interconnected nodes, each of which has a parameter associated therewith with information representing a conditional probability distribution of values of the parameter and wherein the instructions further cause the processor to detect information that represents a change to the information representing the conditional probability distribution.

13. The computer-readable medium of claim 10, wherein the Bayesian network is modeled as a plurality of interconnected nodes, each of which has a parameter associated therewith with information representing evidence that the parameter has a value and wherein the instructions further cause the processor to receive information that is representative of a change in the evidence of a parameter of at least one of the plurality of interconnected nodes.

14. The computer-readable medium of claim 10, wherein the instructions further cause the processor to build the inference engine only when the detected modification is within a portion of the Bayesian network.

15. The computer-readable medium of claim 14, wherein the instructions additionally cause the processor to receive a user specification of the portion of the Bayesian network.

16. The computer-readable medium of claim 10 wherein the instructions further cause the processor to display information about the Bayesian network which can automatically update in response to receipt of information representative of a Bayesian network.

17. A computer system, comprising:

a) a graphical user interface including a display and a user input device,

wherein the display is configured to simultaneously;

display in a first viewing area information reflecting a construction of a belief network; and

display in a second viewing area information reflecting a belief derived from a computation using the belief network; and

wherein the user input device is configured to receive user input based on an interaction with the first viewing area, the user input specifying a modification of the construction of the belief network; and

b) a processor configured to automatically compute information reflecting a modified belief derived from a computation using the belief network as modified according to the user input;

wherein the display is further configured to automatically display in the second viewing area information reflecting the modified belief.

18. The computer system of claim 17, wherein the display is further configured to:

simultaneously display in a third viewing area information reflecting evidence used by the processor to automatically compute the information reflecting the modified belief.

19. The computer system of claim 18, wherein the display is further configured to:

simultaneously display in a third viewing area information reflecting a construction of the Bayesian network, including nodes, interconnections among the nodes and conditional probability distributions for parameters associated with the nodes.

20. The computer system of claim 19, wherein the graphical user interface comprises a modeless user interface that includes user controls for providing the user input without switching modes.

21. The computer system of claim 18, wherein the first viewing area, the second viewing area and the third viewing area provide a modeless user interface for a belief network development application.

22. The computer system of claim 17, wherein each of the first viewing area and the second viewing areas has a control associated with it, and wherein the computer system is further configured to:

a) receive a control input from the user actuating the control associated with the first viewing area or the second viewing area; and

b) in response to receiving the control input from the user, hide the viewing area associated with the actuated control.

23. The computer system of claim 17, wherein each of the first viewing area and the second viewing area has a control associated with it, and wherein the computer system is further configured to:

a) receive a control input from the user actuating the control associated with the first viewing area or the second viewing area;

b) in response to receiving the control input from the user, hide a portion of the information in the viewing area associated with the actuated control.

24. The computer system of claim 17, wherein the user input device is additionally configured to:

a) receive a user input specifying a fixed location of the first viewing area and displaying the first viewing area in the fixed location; and

b) receive user input specifying a floating location of the second viewing area and displaying the second viewing area in the floating location.

25. The computer system of claim 17, wherein the first viewing area comprises a slider control for receiving input concerning evidence that a parameter has a value, and wherein the user input device is additionally configured to:

a) receive an input through the slider control and automatically display in the second viewing area a belief derived from the input received through the slider control.

26. The computer system of claim 25, wherein the computer system is further configured to implement a Bayesian network development application and wherein the display is configured to display the belief derived from the input received through the slider control without switching operating modes of the Bayesian network development application.

27. The computer system of claim 17, wherein:

the belief network is modeled as a plurality of nodes, each having a parameter with a conditional probability distribution associated therewith;

and the user input device is further configured to receive user input specifying a change in the type of a conditional probability distribution of a node.

28. The computer system of claim 17, wherein the processor is configured to automatically compute with an inference engine.

29. The computer system of claim 17, wherein the user interface further comprises a control and the processor is additionally configured to:

a) compute information reflecting a belief in response to user acutation of the control.

30. The computer system of claim 17, wherein the user input device and display are configured to receive user input and automatically display in the second viewing area information reflecting the modified belief in the same user interface mode.