Contextually integrated learning layer

• US 8,694,442 B2
• Filed: 10/07/2011
• Issued: 04/08/2014
• Est. Priority Date: 03/29/2011
• Status: Active Grant

• Current Assignee: Manyworlds Incorporated
• Original Assignee: Manyworlds Incorporated
• Inventors: Flinn, Steven Dennis, Moneypenny, Naomi Felina
• Primary Examiner(s): Gaffin, Jeffrey A
• Assistant Examiner(s): BROWN JR, NATHAN H
• Application Number:
  US13/267,997
• Publication Number:
  US 20120254075A1
• Time in Patent Office: 914 Days
• Field of Search: 706/4
• US Class Current: 706/4
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 40/56 Natural language generation
• CPC Class Codes: G06K 7/10366 the interrogation device being adapted for miscellaneous applications
• CPC Class Codes: G06K 7/10475 arrangements to facilitate interaction with further interrogation devices, e.g. such that at least two interrogation devices may function and cooperate in a network of such devices
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/048 Fuzzy inferencing
• CPC Class Codes: G06N 7/02 using fuzzy logic computing arrangements based on biological models G06N3/00; computing arrangements using knowledge-based models G06N5/00
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A computer-implemented transforming function contextually transforms multiple originating computer-implemented structures into a composite fuzzy network-based structure. The composite fuzzy network-based structure serves as a contextual basis for recommendations. The recommendations may be generated in accordance with inferences of preferences and interests based on usage behaviors. The recommendations may further be generated in accordance with a network neighborhood within the composite fuzzy network-based structure that is based, at least in part, on a navigational context within an originating structure and a user-established navigational neighborhood scope.

Claims

1. A computer-implemented method, comprising:

invoking a first transformational protocol executed on a processor-based computing device, wherein the transformational protocol is applied to transform a computer-implemented non-fuzzy network-based structure within a first originating system into a first computer-implemented fuzzy network-based structure;

invoking a second transformational protocol executed on a processor based computing device, wherein the transformational protocol is applied to transform a computer-implemented non-fuzzy network-based structure within a second originating system into a second computer-implemented fuzzy network-based structure;

invoking a cross-contextualization function, wherein the cross-contextualization function contextually integrates the first fuzzy network-based structure and the second fuzzy network-based structure in accordance with a first usage behavior associated with the first originating system and a second usage behavior associated with the second originating system; and

simulating contextually a user navigating in the second originating system while the user interacts with the first originating system, wherein the contextual simulation is performed through application of the contextually integrated first fuzzy network-based structure and the second fuzzy network-based structure.

2. The method of claim 1, further comprising:

invoking the first transformational protocol, wherein the first transformational protocol is applied to transform a hierarchical-based structure into a fuzzy network-based structure.

3. The method of claim 1, further comprising:

invoking the first transformational protocol, wherein the first transformational protocol is applied to transform a view-based structure into a fuzzy network-based structure.

4. The method of claim 1, further comprising:

invoking the first transformational protocol, wherein the first transformational protocol is applied to transform a tagging-based structure into the first fuzzy network-based structure.

5. The method of claim 1, further comprising:

invoking the cross-contextualization function, wherein the cross-contextualization function contextually integrates the first fuzzy network-based structure and the second fuzzy network-based structure in accordance with a tagging behavior.

6. The method of claim 1, further comprising:

receiving a recommendation generated in accordance with the contextually integrated first fuzzy network-based structure and second fuzzy network-based structure, and a navigational context established within the first originating system.

7. The method of claim 6, further comprising:

receiving the recommendation in accordance with a user-established scope of a navigational neighborhood within the contextually integrated first fuzzy network-based structure and second fuzzy network-based structure.

8. A computer-implemented system, comprising:

a first transforming function executed on a processor-based computing device that applies a first transformational protocol to transform a non-fuzzy network-based structure within a first system into a first computer-implemented fuzzy network-based structure;

a second transforming function executed on a processor-based computing device that applies a second transformational protocol to transform a non-fuzzy network-based structure within a second system into a second computer-implemented fuzzy network-based structure;

a cross-contextualization function that contextually integrates the first fuzzy network-based structure and the second fuzzy network-based structure in accordance with a first usage behavior associated with the first originating system and a second usage behavior associated with the second originating system; and

a contextual simulation function executed on a processor-based system that contextually simulates a user navigating in the second originating system while the user interacts with the first originating system, wherein the contextual simulation is performed through application of the contextually integrated first fuzzy network-based structure and the second fuzzy network-based structure.

9. The system of claim 8, further comprising:

the first transforming function, wherein the first transforming function transforms a hierarchical-based structure into a fuzzy network-based structure.

10. The system of claim 8, further comprising:

the first transforming function, wherein the first transforming function transforms a view-based structure into a fuzzy network-based structure.

11. The system of claim 8, further comprising:

the first transforming function, wherein the first transforming function transforms a tag-based structure into a fuzzy network-based structure.

12. The system of claim 8, further comprising:

the cross-contextualization function, wherein the cross-contextualization function contextually integrates the first fuzzy network-based structure and the second fuzzy network-based structure in accordance with a tagging behavior.

13. The system of claim 8, further comprising:

a recommendation function that generates a recommendation in accordance with the contextually integrated first fuzzy network-based structure and second fuzzy network-based structure, and based, at least in part, on a navigational context established within the first originating system.

14. The system of claim 13, further comprising:

a contextual neighborhood function that provides a user-established scope of a contextual neighborhood to the recommendation function.

15. A computer-implemented system, comprising:

a transforming function executed on a processor-based computing device that transforms a first originating structure comprising a first plurality of objects to a first computer-implemented fuzzy network-based structure and transforms a second originating structure comprising a second plurality of objects to a second computer-implemented fuzzy network-based structure;

a computer-implemented integration function that generates a composite fuzzy network-based structure based, at least in part, on the first fuzzy network-based structure, the second fuzzy network-based structure, and a plurality of usage behaviors;

a contextual simulation function that identifies a first object of the first plurality of objects to serve as a first context for a recommendation to be delivered to a user and that identifies a corresponding second object of the second plurality of objects to serve as a second context for the recommendation, wherein the correspondence between the first object and the second object is performed through application of the composite fuzzy network structure; and

a computer-implemented recommendation function that generates a recommendation for delivery to the user in accordance with the first context, the second context, and an inference that is based, at least in part, on a plurality of behaviors.

16. The system of claim 15, further comprising:

the recommendation function, wherein the recommendation function generates the recommendation in accordance with the inference, wherein the inference is an inference of a preference.

17. The system of claim 15, further comprising:

the recommendation function, wherein the recommendation function generates the recommendation in accordance with the inference, wherein the inference is an inference of a level of expertise.

18. The system of claim 15, further comprising:

the recommendation function, wherein the recommendation function generates the recommendation in accordance with a navigational context established by a user while navigating the first originating structure.

19. The system of claim 15, further comprising:

the recommendation function, wherein the recommendation function generates the recommendation in accordance with a user-established navigational neighborhood scope.

20. The system of claim 15 further comprising:

an explanation function that generates an explanation with regard to the recommendation, wherein the explanation includes a reference to the first originating structure.