SYSTEM AND METHOD FOR MODELING RELATIONSHIPS BETWEEN ENTITIES

• US 20090248738A1
• Filed: 03/31/2008
• Published: 10/01/2009
• Est. Priority Date: 03/31/2008
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Davis, Marc Eliot, Higgins, Christopher William, Martinez, Ronald, O'Sullivan, Joseph James
• Granted Patent: US 8,271,506 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/211 Schema design and management
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification

Abstract

The disclosure describes systems and methods for modeling relationships between entities on a network using data collected from a plurality of communication channels including social data, spatial data, temporal data and logical data within a W4 Network. The W4 Network personalizes and automates sorting, filtering and processing of W4COMN communications delivered or requested to be delivered using personalized value-based ranking and encoding of data, which is modeled from the point-of-view (POV) of any specific user, topic or node in the W4 Distributed graph. POV modeling supplies comparative value services to users which entails individuated data models to be aggregated and used in customization and personalization forecasting for each user and their associated data management needs.

Claims

1. A method for modeling relationships comprising:

identifying a first real world entity (RWE) having a first information object (IO) associated therewith that defines a state of the first RWE, and a second information object associated with the first RWE that defines a state of a second RWE; and

identifying a third information object associated with the second RWE that defines a state of the second RWE, and a fourth information object associated with the second RWE that defines a state of the first RWE, wherein;

in response to a request for state information about the first RWE from a perspective of the second RWE, analyzing the fourth information object,

in response to a request for state information about the second RWE from a perspective of the first RWE, analyzing the second information object,

in response to a request for state information about the first RWE from a perspective of the first RWE, analyzing the first information object, and

in response to a request for state information about the second RWE from a perspective of the second RWE, analyzing the third information object.

2. The method of claim 1 further comprising:

generating an entity information object for each analysis of the information objects with respect to the first RWE state information and the second RWE state information, and wherein each generated entity information object defines a point-of-view (POV) relationship between each of the information objects associated with the first RWE and the second RWE.

3. The method of claim 2 further comprising storing each POV relationship independently.

4. The method of claim 2 further comprising storing the defined POV relationship based upon a respective perspective of the first RWE to the second RWE and the second RWE to the first RWE.

5. The method of claim 2 further comprising identifying the POV relationship as explicit if the POV relationship between the first RWE and the second RWE is based upon identified correlations between the first RWE and the second RWE.

6. The method of claim 2 further comprising identifying the POV relationship as implicit if determined based on modeling of known interactions between the first RWE and the second RWE.

7. The method of claim 6 wherein the modeling comprises a probability analysis of data contained in communications between the first RWE and the second RWE.

8. The method of claim 6 wherein the modeling comprises analysis of content of communications between the first RWE and the second RWE.

9. The method of claim 2 wherein the entity information objects represent the first RWE and the second RWE, the entity information objects comprise corresponding descriptors and identifiers for the first RWE and the second RWE.

10. The method of claim 6 further comprising determining the implicit POV relationship based upon stored social data, spatial data, temporal data and logical data of the first RWE and the second RWE and the information objects associated with the first RWE and second RWE.

11. A computer-readable medium tangibly encoding instructions for performing a method for modeling relationships comprising;

identifying a first real world entity (RWE) associated with a first information object (IO) that defines a state of the first RWE, and a second information object associated with the first RWE and defining a state of a second RWE;

identifying a third information object associated with the second RWE that defines a state of the second RWE, and a fourth information object associated with the second RWE that defines a state of the first RWE, wherein;

in response to a request for state information about the first RWE from a perspective of the second RWE, analyzing the fourth infomiation object,

in response to a request for state information about the second RWE from a perspective of the first RWE, analyzing the second information object,

in response to a request for state information about the first RWE from a perspective of the first RWE, analyzing the first information object, and

in response to a request for state information about the second RWE from a perspective of the second RWE, analyzing the third information object; and

generating an entity information object for each analysis of the information objects with respect to the first RWE state information and the second RWE state information, and wherein each generated entity information object defines a point-of-view (POV) relationship between each of the information objects associated with the first RWE and the second RWE.

12. The computer-readable medium of claim 11 further comprising storing the defined POV relationship based upon a respective perspective of the first RWE to the second RWE and the second RWE to the first RWE.

13. The computer-readable medium of claim 11 further comprising identifying the POV relationship as explicit if the POV relationship between the first RWE and the second RWE is based upon identified correlations between the first RWE and the second RWE.

14. The computer-readable medium of claim 11 further comprising identifying the POV relationship as implicit if determined based on modeling of known interactions between the first RWE and the second RWE.

15. The computer-readable medium of claim 11 wherein the entity information objects represent the first RWE and the second RWE, the entity information objects comprise corresponding descriptors and identifiers for the first RWE and the second RWE.

16. The computer-readable medium of claim 14 further comprising:

determining the implicit POV relationship based upon stored social data, spatial data, temporal data and logical data of the first RWE and the second RWE and the information objects associated with the first RWE and second RWE.

17. A system for modeling relationships comprising:

a correlation engine connected via at least one communication channel to a plurality of computing devices transmitting information objects (IOs) over the at least one communication channel, wherein the correlation engine correlates associations between the IOs and a plurality of real-world entities (RWEs) based upon analysis of extracted social data, spatial data, temporal data and logical data associated with the IOs transmitted over the at least one communication channel; and

a point-of-view (POV) relationship identification engine that identifies POV relationships between the RWEs based upon the correlations made by the correlation engine.

18. The system of claim 17 further comprising:

the POV engine generating an entity IO for the relationships of the RWEs, and wherein each generated entity IO defines the POV relationships between the RWEs.

19. The system of claim 17 further comprising;

the POV engine storing information in the appropriate IOs that represent RWEs associated with the relationship upon determination that at least one of the POV relationships exist.

20. The system of claim 17 further comprising

the POV engine identifying the POV relationships as explicit if the POV relationships between the RWEs are based upon identified correlations between the RWEs.

21. The system of claim 17 further comprising

the POV engine identifying the POV relationships as implicit if determined based on modeling of known interactions between the RWEs.