Adaptive and recursive system and method
A system and method of advertising based on the automatic determination of an advertising recipient's location and inferences of preferences derived from usage behaviors is disclosed. The advertising recipient's location that is considered in delivering a specific advertisement may be the current location or one or more historical locations. Proximity considerations with regard to other people, locations, or physical objects may influence the advertisement that is to be delivered. The advertisement may be delivered to a mobile device that has location-aware capabilities such as a Global Positioning System-based system.
1. An apparatus, comprising:
at least one storage device configured to store:
two or more objects to represent two or more users, respectively;
a usage aspect reflecting a clustering of use and associated usage behaviors of the two or more users interacting with an adaptive system; and
a structural aspect denoting a collection of system objects that are part of the adaptive system, wherein the system objects include one or more computer applications, executable code, or one or more references to the one or more computer applications; and
wherein the adaptive system includes a recommendation function including at least one algorithm usable to generate a recommendation following an update to the structural aspect, wherein the update is based, at least in part, on captured usage information collected by tracking user interactions with the adaptive system;
wherein the apparatus further comprises a processor configured to execute the at least one algorithm, and wherein the at least one algorithm includes:
a preference inferring algorithm to infer preferences based at least in part on the captured usage information, wherein the recommendation is generated based at least in part on the inferred preferences, or
a recommendation optimization algorithm using statistical pattern matching of words, phrases or representations, in written, audio, or pictorial format, within content accessible to the adaptive system, wherein the recommendation is generated based at least in part on a result of the statistical pattern matching.
2. The apparatus of claim 1 , wherein at least one of the usage behaviors is associated with either a user of the two or more users, one or more user communities, or the user and one or more user communities simultaneously, wherein the user comprises a single-member subset of the two or more users and a community of the one or more user communities comprises a multiple-member subset of the two or more users.
3. The apparatus of claim 1 , further comprising a function to generate a social network representation, wherein the social network representation comprises a plurality of users of the two or more users and at least one affinity between different objects of the two or more objects.
4. The apparatus of claim 1 , further comprising a function to determine the at least one affinity, the function to determine the affinity comprising:
means to apply usage behavior categories, wherein the usage behavior categories are selected from a group consisting of navigation and access patterns, collaborative patterns, direct feedback patterns, subscription patterns, self-profiling patterns, reference patterns, physical location patterns, and usage temporal patterns.
5. The apparatus of claim 1 , further comprising:
a structural aspect comprising a fuzzy network structure, wherein the fuzzy network structure comprises a plurality of objects of the two or more objects, wherein the plurality of objects have one or more relationships types, and one or more relationships associated with each relationship type, each relationship being uni-directional or bidirectional, and each direction of each relationship has an associated relationship indicator, wherein the relationship indicators associated with each direction are not necessarily the same magnitude.
6. The apparatus of claim 5 , further comprising a relationship representing a process sequence between a first object and a second object of the plurality of objects.
7. The apparatus of claim 6 , further comprising a function to combine a plurality of process networks.
8. The apparatus of claim 1 , wherein at least one usage behavior of the associated usage behaviors is associated with a user of the two or more users tagging an object of the two or more objects.
9. The apparatus of claim 8 , further comprising a function that automatically modifies the structural element to:
generate a new relationship,
modify an existing relationship, delete an existing relationship, add an object to the two or more objects,
modify an object of the two or more objects, or
delete an object of the two or more objects.
10. The apparatus of claim 1 , wherein the recommendation function is usable to generate a recommendation in response to a request by a user of the two or more users.
11. A method, comprising:
accessing, using a processing device, at least one storage device configured to store:
two or more objects to represent two or more users, respectively;
a usage aspect reflecting a clustering of use and associated usage behaviors of the two or more users interacting with an adaptive system; and
a structural aspect denoting a collection of system objects that are part of the adaptive system, wherein the system objects include one or more computer applications, executable code, or one or more references to the one or more computer applications;
updating the structural aspect of the adaptive system based, at least in part, on captured usage information collected by tracking user interactions with the adaptive system; and
wherein the adaptive system includes a recommendation function including at least one algorithm usable to generate a recommendation following said updating the structural aspect;
wherein the processing device is configured to execute the at least one algorithm, and wherein the at least one algorithm includes:
a preference inferring algorithm to infer preferences based at least in part on the captured usage information, wherein the recommendation is generated based at least in part on the inferred preferences, or
a recommendation optimization algorithm using statistical pattern matching of words, phrases or representations, in written, audio, or pictorial format, within content accessible to the adaptive system, wherein the recommendation is generated based at least in part on a result of the statistical pattern matching.
12. The method of claim 11 , further comprising:
inferring the associated usage behavioral patterns based, at least in part, on changes in the physical location of a user of the two or more users.
13. The method of claim 11 , further comprising:
inferring the associated usage behavioral patterns based, at least in part, on a duration a user of the two or more users remains at a physical location.
14. The method of claim 13 , further comprising:
automatically determining the physical location that is associated with the at least one user by applying a global positioning system.
15. The method of claim 11 , wherein the two or more users include a first user and a second user, and the method further comprises:
inferring the associated usage behavioral patterns based, at least in part, on a physical proximity of the first user to the second user.
16. The method of claim 11 , further comprising:
inferring the associated usage behavioral patterns based, at least on part, on a proximity of a user of the two or more users to a physical object.
17. The method of claim 11 , wherein the generated recommendation includes at least one content object comprising an advertisement.
18. The method of claim 17 , further comprising:
delivering the at least one content object comprising the advertisement to a mobile device associated with a user of the two or more users.
19. The method of claim 18 , further comprising:
recursively updating the structural aspect of the adaptive system based at least in part on tracking user interactions with the at least one content object comprising the advertisement.