METHOD AND APPARATUS FOR INFORMATION CLUSTERING BASED ON PREDICTIVE SOCIAL GRAPHS

• US 20130054604A1
• Filed: 08/30/2011
• Published: 02/28/2013
• Est. Priority Date: 08/30/2011
• Status: Active Grant

• Current Assignee: Nokia Technologies Oy (Nokia Corporation)
• Original Assignee: Nokia Corporation
• Inventors: Boldyrev, Sergey, Kalra, Pavandeep
• Granted Patent: US 9,477,787 B2
• Time in Patent Office: Days
• US Class Current: 707/739
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/906 Clustering; Classification
• CPC Class Codes: G06F 16/907 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually

Abstract

An approach is provided for providing information clustering based on predictive social graphs. An information clustering platform processes and/or facilitates a processing of one or more social graphs associated with one or more users to cause, at least in part, a prediction of one or more future states of the one or more social graphs. The information clustering platform further causes, at least in part, a clustering of one or more data items associated with at least one information space based, at least in part, on the one or more social graphs, the one or more future states, or a combination thereof.

Claims

1. A method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on the following:

a processing of one or more social graphs associated with one or more users to cause, at least in part, a prediction of one or more future states of the one or more social graphs; and

a clustering of one or more data items associated with at least one information space based, at least in part, on the one or more social graphs, the one or more future states, or a combination thereof.

2. A method of claim 1, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

a processing of one or more attributes associated with the one or more users to determine the one or more social graphs, the one or more future states, the one or more data items, or a combination thereof.

3. A method of claim 1, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

at least one sequence of one or more information management processes associated with the one or more data items;

a processing of the at least one sequence to determine one or more process states of the respective one or more information management processes;

at least one determination of one or more information state trajectories based, at least in part, on at least one sequence, the one or more process states, or a combination thereof; and

at least one determination to cause, at least in part, the prediction of the one or more future states based, at least in part, on the one or more information state trajectories.

4. A method of claim 3, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

processing and/or facilitating a process of the one or more information state trajectories, the one or more future states, or a combination thereof to determine recyclability information associated with the one or more data items,

wherein the clustering of the one or more data items is based, at least in part, on the recyclability information.

5. A method of claim 3, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

at least one determination of at least one model state space based, at least in part, on the one or more state trajectories, the one or more process states, or a combination thereof; and

at least one determination to cause, at least in part, the prediction of the one or more future states based, at least in part, on an observation of the at least one model state space.

6. A method of claim 3, wherein the one or more process states include, at least in part, one or more active states, one or more inactive states, one or more transitional states, or a combination thereof, and the one or more information state trajectories include, at least in part, one or more regular motions, one or more stochastic motions, or a combination thereof with respect to the one or more process states.

7. A method of claim 3, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

at least one determination of one or more finite sets of possible future states with respect to one or more points in the future based, at least in part, on the one or more information state trajectories; and

at least one determination to select at least some of the one or more future states from among the one or more finite sets.

8. A method of claim 7, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

a history of utilization of the one or more data items, the at least one information space, or a combination thereof;

a processing of the history to cause, at least in part, an extraction of one or more patterns; and

at least one determination of the one or more finite sets, the one or more possible future states, the one or more future states, or combination thereof based, at least in part, on the one or more patterns.

9. A method of claim 1, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

at least one determination of the one or more information state trajectories based, at least in part, on an inference action, a conceptual clustering, an analogy creation, one or more working conditions, a fault prediction, one or more usage patterns, a workload estimation, or a combination thereof.

10. A method of claim 1, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

a serialization of one or more computation closures associated with the processing of the one or more social graphs, the prediction of the one or more future states, the clustering of the one or more data items, or a combination thereof; and

an association of the serialization with respective ones of the one or more data items, the at least one information space, or a combination thereof.

11. An apparatus comprising:

at least one processor; and

at least one memory including computer program code for one or more programs,

the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following,

process and/or facilitate a processing of one or more social graphs associated with one or more users to cause, at least in part, a prediction of one or more future states of the one or more social graphs; and

cause, at least in part, a clustering of one or more data items associated with at least one information space based, at least in part, on the one or more social graphs, the one or more future states, or a combination thereof.

12. An apparatus of claim 11, wherein the apparatus is further caused to:

process and/or facilitate a processing of one or more attributes associated with the one or more users to determine the one or more social graphs, the one or more future states, the one or more data items, or a combination thereof.

13. An apparatus of claim 11, wherein the apparatus is further caused to:

determine at least one sequence of one or more information management processes associated with the one or more data items;

process and/or facilitate a processing of the at least one sequence to determine one or more process states of the respective one or more information management processes;

determine one or more information state trajectories based, at least in part, on at least one sequence, the one or more process states, or a combination thereof; and

cause, at least in part, the prediction of the one or more future states based, at least in part, on the one or more information state trajectories.

14. An apparatus of claim 13, wherein the apparatus is further caused to:

processing and/or facilitating a process of the one or more information state trajectories, the one or more future states, or a combination thereof to determine recyclability information associated with the one or more data items,

wherein the clustering of the one or more data items is based, at least in part, on the recyclability information.

15. An apparatus of claim 13, wherein the apparatus is further caused to:

determining at least one model state space based, at least in part, on the one or more state trajectories, the one or more process states, or a combination thereof; and

causing, at least in part, the prediction of the one or more future states based, at least in part, on an observation of the at least one model state space.

16. An apparatus of claim 13, wherein the one or more process states include, at least in part, one or more active states, one or more inactive states, one or more transitional states, or a combination thereof, and the one or more information state trajectories include, at least in part, one or more regular motions, one or more stochastic motions, or a combination thereof with respect to the one or more process states.

17. An apparatus of claim 13, wherein the apparatus is further caused to:

determine one or more finite sets of possible future states with respect to one or more points in the future based, at least in part, on the one or more information state trajectories; and

determine to select at least some of the one or more future states from among the one or more finite sets.

18. An apparatus of claim 17, wherein the apparatus is further caused to:

determine a history of utilization of the one or more data items, the at least one information space, or a combination thereof;

process and/or facilitate a processing of the history to cause, at least in part, an extraction of one or more patterns; and

determine the one or more finite sets, the one or more possible future states, the one or more future states, or combination thereof based, at least in part, on the one or more patterns.

19. An apparatus of claim 11, wherein the apparatus is further caused to:

determine the one or more information state trajectories based, at least in part, on an inference action, a conceptual clustering, an analogy creation, one or more working conditions, a fault prediction, one or more usage patterns, a workload estimation, or a combination thereof.

20. An apparatus of claim 11, wherein the apparatus is further caused to:

cause, at least in part, a serialization of one or more computation closures associated with the processing of the one or more social graphs, the prediction of the one or more future states, the clustering of the one or more data items, or a combination thereof; and

cause, at least in part, an association of the serialization with respective ones of the one or more data items, the at least one information space, or a combination thereof.

21-48. -48. (canceled)