Adaptive Digital Asset and Media Management

• US 20070094157A1
• Filed: 11/13/2006
• Published: 04/26/2007
• Est. Priority Date: 04/08/2005
• Status: Abandoned Application

• Current Assignee: Manyworlds Incorporated
• Original Assignee: Manyworlds Incorporated
• Inventors: Moneypenny, Naomi, Flinn, Steven
• Application Number:
  US11/559,222
• Publication Number:
  US 20070094157A1
• Time in Patent Office: Days
• US Class Current: 706/2
• CPC Class Codes: G06F 8/10 Requirements analysis; Specification techniques
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A method and system for adaptive digital asset and media management is disclosed. Online assets and/or their associated structural context within a computer-based system are automatically modified based on assessed values derived from usage behaviors of users of the online assets. Adaptive media instances can be automatically generated, in conjunction with media instance rules and limits, from inferences of preferences derived from usage behaviors of users of computer-based systems. The media instance types that can be generated and managed include text-based, video-based, audio-based, or interactive media such as games.

Claims

1. An adaptive asset management method comprising:

establishing a computer-based system, wherein the computer-based system is comprised of a content aspect comprising information and a structural aspect comprising the content aspect and associated relationships;

capturing usage behaviors associated with the computer-based system, wherein the usage behaviors are associated with one or more users and correspond to a plurality of usage behavior categories;

generating a value for an online asset associated with the computer-based system based, at least in part, on inferences of preferences derived from a plurality of usage behaviors associated with the one or more users and that correspond to a plurality of usage behavior categories; and

modifying the computer-based system in accordance with the value.

2. The method of claim 1, wherein capturing usage behaviors associated with the computer-based system, wherein the usage behaviors are associated with one or more users and that correspond to a plurality of usage behavior categories comprises:

capturing usage behaviors corresponding to predetermined categories of usage behaviors, the predetermined categories of usage behaviors being 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, attention patterns, and usage temporal patterns.

3. The method of claim 1, wherein modifying the computer-based system in accordance with the value comprises:

modifying automatically the online asset.

4. The method of claim 1, wherein modifying the computer-based system in accordance with the value comprises:

modifying automatically the structural aspect.

5. The method of claim 1, further comprising:

managing an asset represented by the online asset.

6. An adaptive media management method comprising:

establishing a computer-based system, wherein the computer-based system is comprised of a content aspect comprising information and a structural aspect comprising the content aspect and associated relationships;

capturing usage behaviors associated with the computer-based system, wherein the usage behaviors are associated with one or more users and that correspond to a plurality of usage behavior categories;

determining one or more media instance limits associated with generating one or more media instances; and

generating a media instance based, at least in part, on inferences of preferences derived from a plurality of usage behaviors associated with the one or more users and that correspond to a plurality of usage behavior categories, and in accordance with the one or more media instance limits.

7. The method of claim 6, wherein capturing usage behaviors associated with the computer-based system, wherein the usage behaviors are associated with one or more users and that correspond to a plurality of usage behavior categories comprises:

capturing usage behaviors corresponding to predetermined categories of usage behaviors, the predetermined categories of usage behaviors being 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, attention patterns, and usage temporal patterns.

8. The method of claim 6, wherein determining one or more media instance limits associated with generating one or more media instances comprises:

determining a media limit, the media limit being selected from a group consisting of number of media instances limit, media instance information limit, and advertising terms and conditions.

9. The method of claim 6, wherein generating a media instance based, at least in part, on inferences of preferences derived from a plurality of usage behaviors associated with the one or more users and that correspond to a plurality of usage behavior categories, and in accordance with the media instance limits comprises:

generating a media type, the media type being selected from a group consisting of a print publication, video, audio, and interactive game.

10. The method of claim 6, wherein generating a media instance based, at least in part, on inferences of preferences derived from a plurality of usage behaviors associated with the one or more users and that correspond to a plurality of usage behavior categories, and in accordance with the media instance limits comprises:

applying terms and conditions of advertisers.

11. The method of claim 6, further comprising:

applying a history of media instance receipts.

12. The method of claim 6, wherein generating a media instance based, at least in part, on inferences of preferences derived from a plurality of usage behaviors associated with the one or more users and that correspond to a plurality of usage behavior categories, and in accordance with the media instance limits comprises:

optimizing the generated media instances with respect to media instance limits and expected overall value to recipients.

13. An adaptive media management system comprising:

a computer-based system, wherein the computer-based system is comprised of a content aspect comprising information and a structural aspect comprising the content aspect and associated relationships;

usage behaviors associated with the computer-based system, wherein the usage behaviors are associated with one or more users and that correspond to a plurality of usage behavior categories;

one or more media instance limits associated with generating one or more media instances; and

a function that generates a media instance based, at least in part, on inferences of preferences derived from a plurality of usage behaviors associated with the one or more users and that correspond to a plurality of usage behavior categories, and in accordance with the one or more media instance limits.

14. The system of claim 13, wherein usage behaviors associated with the computer-based system, wherein the usage behaviors are associated with one or more users and that correspond to a plurality of usage behavior categories comprises:

usage behaviors corresponding to predetermined categories of usage behaviors, the predetermined categories of usage behaviors being 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, attention patterns, and usage temporal patterns.

15. The system of claim 13, wherein one or more media instance limits associated with generating one or more media instances comprises:

a media limit, the media limit being selected from a group consisting of number of media instances limit, media instance information limit, and advertising terms and conditions.

16. The system of claim 13, wherein a function that generates a media instance based, at least in part, on inferences of preferences derived from a plurality of usage behaviors associated with the one or more users and that correspond to a plurality of usage behavior categories, and in accordance with the media instance limits comprises:

a function that generates a media instance type, the function that generates a media instance type being selected from a group consisting of a function that generates a print media instance, a function that generates a video media instance, a function that generates an audio media instance, and a function that generates an interactive game media instance.

17. The system of claim 13, wherein a function that generates a media instance based, at least in part, on inferences of preferences derived from a plurality of usage behaviors associated with the one or more users and that correspond to a plurality of usage behavior categories, and in accordance with the media instance limits comprises:

means to align media instances with the terms and conditions of advertisers.

18. The system of claim 13, further comprising:

a history of media instance deliveries.

19. The system of claim 13, further comprising:

a history of media instance receipts.

20. The system of claim 13, wherein a function that generates a media instance based, at least in part, on inferences of preferences derived from a plurality of usage behaviors associated with the one or more users and that correspond to a plurality of usage behavior categories, and in accordance with the media instance limits comprises:

means to optimize the generated media instances with respect to media instance limits and expected collective value to recipients.