Universal data discernment

• US 8,738,562 B2
• Filed: 09/26/2013
• Issued: 05/27/2014
• Est. Priority Date: 10/02/2008
• Status: Active Grant

• Current Assignee: Global Healthcare Exchange (GHX Ultimate Parent Corp.)
• Original Assignee: Global Healthcare Exchange (GHX Ultimate Parent Corp.)
• Inventors: Oaten, Philip J., Davis, Lou A.
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US14/038,457
• Publication Number:
  US 20140025622A1
• Time in Patent Office: 243 Days
• Field of Search: None
• US Class Current: 706/51
• CPC Class Codes: G06N 3/084 Backpropagation, e.g. using gradient descent
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

An contextual artificial intelligence system is disclosed. Intelligent business objects enable dynamic data object interaction and encapsulation of user context. Data is rationalized and data objects evolve by way of an artificial intelligence assisted process of self-discovery. Significant data is identified based upon factors such as cost, revenue and outcome and contextually significant result sets are automatically generated for users.

Claims

1. A computer-based method comprising:

analyzing, by a data discernment computer, first input data;

identifying, by the computer and based upon the analyzing, first item information associated with a first item;

analyzing, by the computer, a master database to identify a first relationship between the first item and a first existing item, wherein the first existing item is one of a plurality of existing items; and

creating, by the computer, a first intelligent business object (IBO) to store at least one of;

at least a portion of the first item information and the first relationship.

2. The computer-based method of claim 1, further comprising determining, by the computer, a first context of the first item.

3. The computer-based method of claim 2, wherein the first context is based upon at least one of:

the first input data, a second input data, the first item information, the first relationship, a first data source, a supplier of the first item, a cost structure of the first item, a function of the first item, a manufacturer of the item, a complimentary item that is complimentary to the first item, a substitute item that is a substitute to the first time, and a user of the item.

4. The computer-based method of claim 2, further comprising creating, by the computer, a first intelligent context object (ICO) to store the first context.

5. The computer-based method of claim 1, further comprising creating, by the computer, a first intelligent relationship object (IRO) to store a relationship between the first IBO and a second IBO.

6. The computer-based method of claim 5, wherein the creating the first IRO is in response to at least one of:

an external event, a user input, a data input, a change in value of the first IBO, or a change in value of the second IBO.

7. The computer-based method of claim 5, wherein the first IRO comprises at least one of:

an independent relationship, a dependent relationship, or an interdependent relationship.

8. The computer-based method of claim 1, further comprising creating, by the computer, a first intelligence memory object (IMO).

9. The computer-based method of claim 8, wherein the IMO includes data for an energy value data, a context, and a time.

10. The computer-based method of claim 9, wherein the creating the first IMO is in response to a significance level for the IMO data exceeding a threshold level.

11. The computer-based method of claim 8, further comprising creating, by the computer, a first Intelligent Spatial Object (ISO) for the time data of the IMO.

12. The computer-based method of claim 1, further comprising calculating, by the computer, a probability of fitness (POF) for the first IBO.

13. The computer-based method of claim 12, further comprising determining, by the computer and based upon the POF, whether to make the first IBO available to a consumer.

14. The computer-based method of claim 1, further comprising using, by the computer, a belief system to control evolution of the first IBO.

15. The computer-based method of claim 14, wherein the belief system comprises a plurality of operating levels.

16. The computer-based method of claim 15, further comprising using, by the computer, the belief system to determine that the first IBO inherits data from a second IBO.

17. A computer-based method comprising:

analyzing, by the computer, a profile of a user;

creating, by the computer and based upon the analyzing, a user context; and

storing, by the computer, the user context in an intelligent context object (ICO).

18. The computer-based method of claim 17, wherein the user profile comprises at least one of:

a job function, a personality profile, a user preference, a user history, or a user action.

19. The computer-based method of claim 17, farther comprising:

using, by the computer, the user context to identify one or more intelligent business objects (IBOs) of interest to the user; and

creating, by the computer, a result set of the identified one or more IBOs.

20. The computer-based method of claim 19, further comprising tailoring, by the computer, the result set of IBOs based on the user context.