Dynamic Characterization of Nodes in a Semantic Network for Desired Functions Such As Search, Discovery, Matching, Content Delivery, and synchronization of Activity and Information

• US 20090070490A1
• Filed: 11/08/2007
• Published: 03/12/2009
• Est. Priority Date: 11/08/2006
• Status: Active Grant

• Current Assignee: Cricket Media Services Incorporated
• Original Assignee: Cricket Media Services Incorporated
• Inventors: Gilburne, Miles R., Dozier, Linda T., Zolt, Nina, Fish, Edmund J.
• Granted Patent: US 10,547,698 B2
• Time in Patent Office: Days
• US Class Current: 709/248
• CPC Class Codes: G06F 16/90 Details of database functions independent of the retrieved data types
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/08 Auctions
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: G09B 19/22 Games, e.g. card games
• CPC Class Codes: H04L 41/0893 Assignment of logical groups to network elements
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

The present invention provides a system of computers on a wide area network that establishes connections between nodes on the basis of their multidimensional similarity at a particular point in time in a certain setting, such as a social learning network, and sends relevant information to the nodes. Dimensions in the definition of similarity include a plurality of attributes in time and community space. Examples of such dimensions and attributes may include a position in a learning community'"'"'s project cycle, titles of readings and projects, the genre or subject matter under consideration, age, grade or skill level of the participants, and language. The network'"'"'s nodes are represented as a vector of attributes and are searched efficiently and adaptively through a variety of multidimensional data structures and mechanisms. The system includes synchronization that can transform a participant'"'"'s time attributes on the network and coordinate the activities and information for each participant.

Claims

1. A method for synchronizing nodes on a network, said method comprising the steps of:

a. defining a structured environment;

b. identifying relative positions for multiple nodes within the structured environment;

c. synchronizing the multiple nodes based on the relative positions, where the identification of the relative positions and the synchronization are performed without reference to actual time; and

d. serving events based on the positions.

2. The method of claim 1 further comprising re-synchronizing the multiple nodes to allow for changes in the relative positions of the nodes and then serving events based on the re-synchronization.

3. The method of claim 1 wherein the identification of relative positions for multiple nodes occurs continuously to allow for re-synchronization.

4. A method for synchronizing nodes on a network, said method comprising the steps of:

a. defining a structured environment;

b. identifying relative positions for multiple nodes within the structured environment;

c. synchronizing the multiple nodes based on the relative positions, where the structured environment is created by one or more of the nodes; and

d. serving events based on the positions.

5. The method of claim 4 further comprising re-synchronizing the multiple nodes to allow for changes in the relative positions of the nodes and then serving events based on the re-synchronization.

6. The method of claim 4 wherein the identification of relative positions for multiple nodes occurs continuously to allow for re-synchronization.

7. A method for synchronizing nodes on a network, said method comprising the steps of:

a. defining a structured environment;

b. identifying relative positions for multiple interdependent nodes within the structured environment;

c. synchronizing the multiple nodes based on the relative positions;

d. allowing at least one of the relative positions for at least one of the multiple interdependent nodes to change, thereby causing at least one of the relative positions for one of the other multiple interdependent nodes to also change; and

e. serving events based on the positions.

8. The method of claim 7 wherein at least one first selected interdependent node cannot change at least one second selected interdependent node.

9. A method for synchronizing nodes on a network, said method comprising the steps of:

a. collecting event information from multiple node locations;

b. deriving a structured environment from the collected information;

c. associating multiple nodes with the structured environment; and

d. serving one or more events to the multiple nodes based on the structured environment.

10. The method of claim 9 further comprising the step of creating a community of multiple nodes based on at least one of the events served.

11. The method of claim 9 further comprising the step of creating a community of multiple nodes based on participation in an event served.

12. The method of claim 9 further comprising calculating a relative distance between the nodes based on a set of attributes corresponding to the nodes.

13. A method for calculating a comparative distance for each pair of a plurality of nodes on a network, wherein each node comprises a plurality of attributes and each attribute includes a value comprising the steps of:

a. identifying a plurality of attributes corresponding to each node of the plurality of nodes;

b. comparing a first attribute corresponding to a first node to a first attribute corresponding to a second node, wherein the comparison comprises determining a relative difference between the first attribute of the first node and the first attribute of the second node;

c. repeating step (b) for each attribute corresponding to the second node;

d. repeating steps (b) and (c) for each attribute corresponding to the first node; and

e. calculating the comparative distance based on a plurality of relative differences determined at the step (b).

14. The method of claim 13 wherein the determining a relative difference at step (b) comprises representing the value of each attribute as a scalar number.

15. The method of claim 14 wherein the representing a value of each attribute as a scalar number comprises semantically comparing the value to a predefined value contained in a semantic database.

16. The method of claim 13 further comprising the step of weighting each relative difference determined at step (b).

17. The method of claim 16 further comprising the step of dynamically altering the weight applied to each relative difference.

18. The method of claim 13 further comprising dynamically altering the identification of the plurality of attributes at step (a).

19. The method of claim 13 wherein the first node and the second node are part of a subset of the plurality of nodes, wherein the subset is identified based on at least one of the plurality of attributes.

20. The method of claim 13 further comprising repeating steps (a) through (e) for each of the plurality of nodes.

21. The method of claim 20 further comprising graphically displaying the comparative distances calculated at the steps (e).