BAYESIAN BELIEF NETWORK QUERY TOOL

• US 20090106734A1
• Filed: 10/23/2008
• Published: 04/23/2009
• Est. Priority Date: 10/23/2007
• Status: Abandoned Application

• Current Assignee: Gursel Serpen, Michael Jason Riesen
• Original Assignee: Gursel Serpen, Michael Jason Riesen
• Inventors: Riesen, Michael J., Serpen, Gursel
• Application Number:
  US12/256,743
• Publication Number:
  US 20090106734A1
• Time in Patent Office: Days
• US Class Current: 717/104
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks

Abstract

A dataset query tool is disclosed, the query tool including a dataset having a plurality of attributes, wherein each of the attributes has one of a plurality of potential values, a processor adapted to develop a model of the dataset and calculate a posterior probability of at least one of the attributes of the dataset, wherein the model represents an approximation of the joint probability distribution of the dataset, a user interface in communication with the processor, wherein the user interface provides a means for a user to selectively identify values for at least one of the attributes of the dataset and selectively query at least one of the other attributes for a posterior probability calculation based on the identified values.

Claims

1. A dataset query tool comprising:

a dataset having a plurality of attributes, wherein each of the attributes has one of a plurality of potential values;

a processor adapted to receive the dataset, develop a model of the dataset, and calculate a posterior probability of at least one of the attributes of the dataset, wherein the model represents an approximation of the joint probability distribution of the dataset; and

a user interface in communication with the processor, wherein the user interface provides a means for a user to selectively identify values for at least one of the attributes of the dataset and selectively query at least one of the other attributes for a posterior probability calculation based on the identified values.

2. The dataset query tool according to claim 1, wherein the dataset is at least one of a victimization dataset, a criminal profiling dataset, and a crime incident-based dataset.

3. The dataset query tool according to claim 1, wherein the processor includes at least one of a first software code for developing a model of the dataset and a second software code for calculating the posterior probability of at least one of the attributes based on the indentified values.

4. The dataset query tool according to claim 1, wherein the model is a Bayesian Belief Network.

5. The dataset query tool according to claim 1, wherein the user interface is a graphical user interface.

6. The dataset query tool according to claim 1, wherein the user interface is a web application.

7. The dataset query tool according to claim 1, wherein the processor includes a storage device for storing a catalog of pre-generated models to be accessed and queried.

8. A method for querying a dataset, the method comprising the steps of:

providing a dataset having a plurality of attributes, wherein each of the attribute has one of a plurality of potential values;

developing a model to represent an approximation of the joint probability distribution of the dataset;

identifying an evidence;

querying a focus attribute of the dataset to determine a posterior probability of the focus attribute based on the identified evidence.

9. The method according to claim 8, wherein the dataset is at least one of a victimization dataset, a criminal profiling dataset, and a crime incident-based dataset.

10. The method according to claim 8, further comprising the step of providing at least one of a first software code for developing a model of the dataset and a second software code for calculating the posterior probability of at least one of the attributes based on the evidence.

11. The method according to claim 8, wherein the model is a Bayesian Belief Network.

12. The method according to claim 8, further comprising the step of providing a user interface for interacting with the model.

13. The method according to claim 12, wherein the user interface is a graphical user interface.

14. The method according to claim 12, wherein the user interface is a web application.

15. The method according to claim 8, further comprising the step of providing a storage device for storing a catalog of pre-developed models to be accessed and queried.

16. The method according to claim 8, further comprising the step of implementing a rule-generation algorithm to generate a list of potential queries.

18. The method according to claim 8, wherein the model is a Bayesian Belief Network.

19. The method according to claim 12, wherein the user interface is a web application.

20. The method according to claim 8, further comprising the step of implementing a rule-generation algorithm to generate a list of potential queries.

17. A method for querying a dataset, the method comprising the steps of:

providing a model representing an approximation of the joint probability distribution of a dataset;

providing a user interface for interacting with the model;

providing values for a subset of the attributes represented in the model;

querying a focus attribute of the dataset to determine a posterior probability of the focus attribute based on the provided values for the subset of the attributes.