Systems and methods for virtual population mutual relationship management using electronic computer driven networks

• US 20020055833A1
• Filed: 08/13/2001
• Published: 05/09/2002
• Est. Priority Date: 08/23/1999
• Status: Abandoned Application

• Current Assignee: Digital Connexxions Corp. (Omaha Holdco Incorporated)
• Original Assignee: Digital Connexxions Corp. (Omaha Holdco Incorporated)
• Inventors: Sterling, Deborah
• Application Number:
  US09/928,956
• Publication Number:
  US 20020055833A1
• Time in Patent Office: Days
• US Class Current: 703/22
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A method and system for creating and managing Virtual Population mutual relationships is disclosed. The method uses a Rich Semantic Model component, expert system components, and various interface components and other components to dynamically alter the visitation experience as received by the Visitor at a computer and to allow the Visitor control over their Virtual Representative that controls this personal experience.

Claims

1. A method for dynamically creating and managing mutual relationships between a virtual visitor and a virtual enterprise expert on an electronic network, comprising the steps of:

(i) Providing a virtual population, the semantic model of which is rendered specific to one or more real world populations, said virtual population comprising instances of said model;

(ii) Providing expert system software which effects a virtual enterprise expert, said software tailored to a particular virtual population; and

(iii) Applying said expert system software to an instance of said semantic model to create a unique virtual visitation experience.

2. The method of claim 1, wherein said expert system software which effects a virtual enterprise expert is capable of learning about said virtual population.

3. The method of claim 1, wherein said expert system software which effects a virtual enterprise expert intelligently optimizes enterprise goals.

4. The method of claim 1, wherein said expert system software which effects a virtual enterprise expert is further capable of generating new rules.

5. The method of claim 1, wherein said expert system software which effects a virtual enterprise expert comprises an inference or a reasoning engine.

6. The method of claim 1, wherein said expert system software which effects a virtual enterprise expert further comprises a set of rules representative of enterprise expert knowledge.

7. The method of claim 1, wherein said expert system software which effects a virtual enterprise expert contains reasoning engine log information, wherein said reasoning engine log information may store self-observational expert events and learned information.

8. The method of claim 1, wherein said expert system software which effects a virtual enterprise expert is capable of making rule suggestions.

9. The method of claim 1, wherein said expert system software which effects a virtual enterprise expert is programmatically accessible to outside systems.

10. The method of claim 1, wherein said expert system software which effects a virtual enterprise expert is capable of additional functions such as rule ordering to control execution.

11. The method of claim 1, wherein said semantic model comprises fact information selected from classes comprising simple facts, behavioral facts, preference facts, and combinations thereof.

12. The method of claim 1, wherein said semantic model includes universal facts.

13. The method of claim 1, wherein said semantic model further includes enterprise-specific facts.

14. The method of claim 1, wherein said semantic model further includes custom enterprise-specific facts.

15. The method of claim 1, wherein said semantic model further includes facts which are restricted for use by the real world user.

16. The method of claim 1, further including the step of providing a report generator for reporting on one or more of the following activities:

(i) expert activity;

(ii) rules used;

(iii) rule success, (iv) rules suggested; and

(v) learnings.

17. The method of claim 1, wherein said virtual enterprise expert is an e-commerce expert.

18. The method of claim 1, wherein said semantic model is a model of consumers.

19. The method of claim 1, wherein said semantic model includes facts which reflect whether the real world visitor is a known or anonymous visitor.

20. The method of claim 1, wherein said method employs one or more computer systems, said computer systems including one or more user site computers, one or more visit site computers, and one or more populations site computers.

21. The method of claim 1, wherein said virtual population is stored, retrievable, and updateable through a machine-readable database.

22. The method of claim 1, wherein said virtual population is stored, retrievable, and updateable at a site where said virtual population resides.

23. The method of claim 1, wherein said expert system software which effects said virtual enterprise expert includes expert knowledge.

24. The method of claim 1, wherein said virtual enterprise expert is an expert in the marketing and/or selling of goods and services.

25. The method of claim 1, wherein said enterprise expert is deployed on a customer-hosted computer.

26. The method of claim 1, wherein said electronic communication network is a private IP network.

27. The method of claim 1, wherein said electronic communication network is a public IP network or the World Wide Web.

28. The method of claim 1, wherein said electronic communication network is a combination of public and private IP networks.

29. The method of claim 1, wherein there are multiple enterprise sites and one population site.

30. The method of claim 1, further including the step of providing a rule editor.

31. The method of claim 30, wherein said rule editor is capable of a point-and-click style interface.

32. The method of claim 1, further including the step of providing a content management system, wherein said content management system is capable of performing one or more of the following:

storing, viewing, labeling, and annotating arbitrary content available for personalization decisions.

33. The method of claim 32, further including the step of making-labels resulting from said labeling of content available for rule decisions.

34. The method of claim 32, wherein said content management system manages pointers to said content.

35. The method of claim 1, further including the step of providing a billing system.

36. The method of claim 35, wherein said billing system is capable of billing based on rule success.

37. The method of claim 35, wherein said billing system is capable of billing based on successful use of real world visitor identification, said real world visitor identification including one or more identification of population instances, identification with specific facts, identification with custom facts, and identification with some number of facts.

38. The method of claim 1, wherein access to said expert system software is provided as a software plugin with an Application Programmer Interface.

39. The method of claim 1, further including the step of providing expert system software which effects a virtual population expert, said virtual population expert tailored to a particular virtual population.

40. The method of claim 39, wherein said expert system software which effects a virtual population expert is further capable of generating new rules.

41. The method of claim 39, where said expert system software which effects a virtual population expert comprises an inference or a reasoning engine.

42. The method of claim 39, wherein said expert system software which effects a virtual population expert further comprises a set of rules representative of population expert knowledge.

43. The method of claim 39, wherein said expert system software which effects a virtual population expert contains reasoning engine log information, wherein said reasoning engine log information may store self-observational expert events and learned information.

44. The method of claim 39, wherein said expert system software which effects a virtual population expert is capable of making rule suggestions.

45. The method of claim 39, wherein said expert system software which effects a virtual population expert is programmatically accessible to outside systems.

46. The method of claim 39, wherein said expert system software which effects a virtual population expert is capable of additional functions such as rule ordering to control execution.

47. The method of claim 39, wherein said expert system software which effects a virtual population expert is capable of learning new information about said virtual population.

48. The method of claim 39, wherein said expert systems software which effects a virtual population expert is capable of predicting new information about said virtual population.

49. The method of claim 39, wherein said virtual population expert is a consumer population expert.

50. The method of claim 1, further including the step of providing expert system software which effects a virtual visitor expert.

51. The method of claim 50, further including the step of providing a visitor tool, wherein said virtual visitor expert assists a real world visitor in managing an instance of said virtual population that corresponds to a real world visitor through said visitor tool.

52. The method of claim 50, wherein said expert system software which effects a virtual visitor expert is further capable of generating new rules.

53. The method of claim 50, where said expert system software which effects a virtual visitor expert comprises an inference or a reasoning engine.

54. The method of claim 50, wherein said expert system software which effects a virtual visitor expert further comprises a set of rules representative of visitor expert knowledge.

55. The method of claim 50, wherein said expert system software which effects a virtual visitor expert contains reasoning engine log information, wherein said reasoning engine log information may store self-observational expert events and learned information.

56. The method of claim 50, wherein said expert system software which effects a virtual visitor expert is capable of making rule suggestions.

57. The method of claim 50, wherein said expert system software which effects a virtual visitor expert is programmatically accessible to outside systems.

58. The method of claim 50, wherein said expert system software which effects a virtual visitor expert is capable of additional functions such as rule ordering to control execution.

59. The method of claim 50, wherein said virtual visitor expert interacts with said real world visitor through said visitor tool to gain self-consistent knowledge of said real world visitor.

60. The method of claim 50, wherein said virtual visitor expert interacts with said real world visitor through said-visitor tool to learn new knowledge of said real world visitor based on expert knowledge of said virtual population.

61. The method of claim 50, wherein said virtual visitor expert interacts with said real world visitor through said visitor tool to restrict access to at least some information in said instance under the control of said real world user.

62. The method of claim 50, wherein said virtual visitor expert is a consumer visitor expert.

63. A method for dynamically creating and managing mutual relationships between a virtual visitor and a virtual enterprise expert on an electronic network, comprising the steps of:

(i) Providing a virtual population, the semantic model of which is rendered specific to one or more real world populations, said virtual population comprising instances of said model;

(ii) Providing software accessible to a real world enterprise expert, said software permitting said real world expert to create one or more expert rules which can be applied to instances of said semantic model;

(iii) Providing expert system software which effects a virtual enterprise expert, said software tailored to a particular virtual population; and

(iv) Applying said expert system software to an instance of said semantic model to create a unique virtual visitation experience in accordance with the real world expert rules, the interests and/or desires of the visitor, and the expert knowledge of the expert system software.

64. The method of claim 63, wherein access to said expert system software is provided as a software plugin.

65. The method of claim 64, wherein said plugin is provided with an Application Programmer Interface as an extension of a web programming environment.

66. The method of claim 65, further including an Application Programmer Interface call, wherein said call provides access to said virtual enterprise expert whose judgements decide upon web page real estate to be shown to a virtual visitor.

67. The method of claim 66, wherein multiple Application Programmer Interface calls are used on multiple web pages to manage web page content.

68. The method of claim 65, further including an Application Programmer Interface call which provides access to a virtual enterprise expert, wherein said virtual enterprise expert will intelligently add new information to a virtual representative.

69. The method of claim 68, wherein said new information is sent over said electronic communication network to intelligently update said virtual population instance corresponding to said visitor.

70. The method of claim 63, wherein said virtual population instance is automatically retrieved over said electronic network.

71. The method of claim 70, wherein a real world visitor corresponding to said virtual population instance is identified electronically.

72. The method of claim 71, wherein said real world visitor corresponding to said virtual population instance is identified electronically using cookies, e-wallet technology, or other electronic identification mechanisms.

73. The method of claim 65, wherein said Application Programmer Interface further comprises a parameter which allows for a default piece of content to be displayed.

74. The method of claim 63, further including web-based versions of one or more of the following:

(i) rule editor;

(ii) report generator; and

(iii) content management system.

78. The system of claim 74, wherein said expert system is operating in response to a virtual visit at said network site and resulting in the receipt by the user, in real time, of unique digitally managed sensory content at the local computer.

75. A system for dynamically creating and managing mutual relationships between a virtual visitor and a virtual enterprise expert on an electronic network, comprising:

(i) A virtual population, the semantic model of which is rendered specific to one or more real world populations, said virtual population comprising instances of said model; and

(ii) Software accessible to a real world enterprise expert, said software permitting said real world expert to create one or more expert rules which can be applied to instances of said semantic model; and

(iii) Expert system software which effects a virtual enterprise expert, said software tailored to a particular virtual population;

wherein the application of said expert system software to an instance of said semantic model creates a unique virtual visitation experience in accordance with the real world rules, the interests and/or desires of the visitor, and the expert knowledge of the expert system software.

76. A system for conducting real-time dynamic marketing on the Internet comprising:

(i) A web site which contains information which can be dynamically altered and made available to a web site visitor;

(ii) Expert system software which effects a virtual enterprise expert, said software tailored to a particular virtual population; and

(iv) A stored, retrievable, and updateable virtual population accessible through a machine-readable database, the semantic model of which is rendered specific to one or more real world populations, said virtual population comprising instances of said model.

77. A system for creating and maintaining a virtual mutual relationship, said system being accessed by a user through a network by one or more networked computers and comprising:

(i) A database comprising a richly semantically modeled virtual population;

(ii) One or more expert systems in communication with said database and said software associated with a network site, said expert systems(s) being capable of performing at least one or more of the following tasks;

(a.) applying expert rules to instances of said semantically modeled population to produce a reasoned result;

(b.) applying expert system knowledge to instances of said semantically modeled population to produce a reasoned result;

(c.) observing and understanding its own activity;

(d.) learning new information as such information is generated;

(e.) creating new expert rules automatically; and

(f.) reporting on (a)-(e) above.