Methods and apparatus for using task models to help computer users complete tasks

• US 6,606,613 B1
• Filed: 06/03/1999
• Issued: 08/12/2003
• Est. Priority Date: 06/03/1999
• Status: Expired due to Term

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Ingerman, David, Wu, Lani F., Altschuler, Steven J., Jung, Edward K., Ridgeway, Greg
• Primary Examiner(s): STARKS, WILBERT L
• Application Number:
  US09/325,168
• Time in Patent Office: 1,531 Days
• Field of Search: 706/21, 707/3, 707/6, 345/707
• US Class Current: 706/21
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99936 Pattern matching access

Abstract

Methods and apparatus for analyzing tasks performed by computer users by (i) gathering usage data, (ii) converting logged usage data into a uniform format, (iii) determining or defining task boundaries, and (iv) determining a task analysis model by “clustering” similar tasks together. The task analysis model may be used to (i) help users complete a task (such help, for example, may be in the form of a gratuitous help function), and/or (ii) to target marketing information to users based on user inputs and the task analysis model. The present invention also provides a uniform semantic network for representing different types of objects in a uniform way.

Claims

1. A method for using a predetermined model of clustered tasks, for providing help to a user attempting to perform a task, the method comprising steps of:

a) logging inputs of the user as steps;

b) generating a partial task from the steps logged;

c) determining a distance between the partial task generated and each of the clustered tasks;

d) determining a minimum of the distances determined; and

e) rendering help content to the user, wherein the help content is related to a task cluster associated with the minimum of the distances determined.

2. The method of claim 1 wherein the help content is a script of steps for accomplishing the task.

3. The method of claim 1 wherein the help content is a script of steps for completing the partial task.

4. The method of claim 1 wherein the help content is a query for accomplishing the task.

5. The method of claim 1 wherein the help content is a query for completing the partial task.

6. The method of claim 1 wherein the user input are at least one of a query and a command, and

wherein the step of determining a distance between the partial task generated and each of the clustered tasks includes sub-steps of:

i) formatting the steps corresponding to the user input as a run time graph having vertices corresponding to the at least one of the query and the command and having edges corresponding to related queries and commands; and

ii) determining a distance between the run time graph and graphs of tasks of the task clusters of the model.

7. The method of claim 6 wherein the sub-step of determining distances between the run time graph and the graphs of tasks of the task clusters of the model includes steps of:

A) determining an intersection of the run time graph and each of the graphs of the tasks of the task clusters of the model;

B) determining a difference of the run time graph and each of the graphs of the tasks of the task clusters of the model;

C) determining connected elements of each of the differences; and

D) determining, in each case, the distance based on the connected elements and the intersection, wherein the distance increases as a number of the connected elements increases.

8. The method of claim 7 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(A,B\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B.

9. The method of claim 7 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(A,B\right)=\frac{\max <br><br>\left[d^{*}<br><br>\left(A,B\right),d^{*}<br><br>\left(B,A\right)\right]}{n_{\mathrm{intersect}}}$

wherein n_intersect is the number of vertices and edges in A∩

B,

wherein $d^{*}<br><br>\left(A,B\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>e_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B, and,

wherein $d^{*}<br><br>\left(B,A\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i^1<br><br>}$

where v is a parameter greater than 1 and c′

_i is the number of connected elements in piece i of the difference graph B−

A.

10. A method for using a predetermined model of clustered tasks, for providing help to a user attempting to perform a task, the method comprising steps of:

a) logging inputs of the user as steps;

b) generating a partial task from the steps logged;

c) determining a distance between the partial task generated and each of the clustered tasks;

d) determining a minimum of the distances determined;

e) querying the user whether they want to help; and

f) if the user indicates that they want help, rendering help content to the user, wherein the help content is related to a task cluster associated with the minimum of the distances determined.

11. The method of claim 10 wherein the help content is a script of steps for accomplishing the task.

12. The method of claim 10 wherein the help content is a script of steps for completing the partial task.

13. The method of claim 10 wherein the help content is a query for accomplishing the task.

14. The method of claim 10 wherein the help content is a query for completing the partial task.

15. The method of claim 10 wherein the user input are at least one of a query and a command, and

wherein the step of determining a distance between the partial task generated and each of the clustered tasks includes sub-steps of:

i) formatting the steps corresponding to the user input as a run time graph having vertices corresponding to the at least one of the query and the command and having edges corresponding to related queries and commands; and

ii) determining a distance between the run time graph and graphs of tasks of the task clusters of the model.

16. The method of claim 15 wherein the sub-step of determining distances between the run time graph and the graphs of tasks of the task clusters of the model includes steps of:

A) determining an intersection of the run time graph and each of the graphs of the tasks of the task clusters of the model;

B) determining a difference of the run time graph and each of the graphs of the tasks of the task clusters of the model;

C) determining connected elements of each of the differences; and

D) determining, in each case, the distance based on the connected elements and the intersection, wherein the distance increases as a number of the connected elements increases.

17. The method of claim 16 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(A,B\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B.

18. The method of claim 16 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(A,B\right)=\frac{\max <br><br>\left[d^{*}<br><br>\left(A,B\right),d^{*}<br><br>\left(B,A\right)\right]}{n_{\mathrm{intersect}}}$

wherein n_intersect is the number of vertices and edges in A∩

B

wherein $d^{*}<br><br>\left(A,B\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>e_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B, and,

wherein $d^{*}<br><br>\left(B,A\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i^1<br><br>}$

where v is a parameter greater than 1 and c′

_i is the number of connected elements in piece i of the difference graph B−

A.

19. A method for using a predetermined model of clustered tasks, for providing help to a user attempting to perform a task, the method comprising steps of:

a) logging inputs of the user as steps;

b) generating a partial task from the steps logged;

c) determining a distance between the partial task generated and each of the clustered tasks;

d) determining a minimum of the distances determined; and

e) if the minimum of the distances is less than a predetermined threshold, rendering help content to the user, wherein the help content is related to a task cluster associated with the minimum of the distances determined.

20. The method of claim 19 wherein the help content is a script of steps for accomplishing the task.

21. The method of claim 19 wherein the help content is a script of steps for completing the partial task.

22. The method of claim 19 wherein the help content is a query for accomplishing the task.

23. The method of claim 19 wherein the help content is a query for completing the partial task.

24. The method of claim 19 wherein the user input are at least one of a query and a command, and

wherein the step of determining a distance between the partial task generated and each of the clustered tasks includes sub-steps of:

i) formatting the steps corresponding to the user input as a run time graph having vertices corresponding to the at least one of the query and the command and having edges corresponding to related queries and commands; and

ii) determining a distance between the run time graph and graphs of tasks of the task clusters of the model.

25. The method of claim 24 wherein the sub-step of determining distances between the run time graph and the graphs of tasks of the task clusters of the model includes steps of:

A) determining an intersection of the run time graph and each of the graphs of the tasks of the task clusters of the model;

B) determining a difference of the run time graph and each of the graphs of the tasks of the task clusters of the model;

C) determining connected elements of each of the differences; and

D) determining, in each case, the distance based on the connected elements and the intersection, wherein the distance increases as a number of the connected elements increases.

26. The method of claim 25 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\left(A,B\right)=\underset{i\in <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B.

27. The method of claim 25 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\left(A,B\right)=\frac{\max <br><br>\text{\hspace{1em}<br><br>}\left[d^{*}<br><br>\left(A,B\right),d^{*}<br><br>\left(B,A\right)\right]}{n_{\mathrm{intersect}}}$

wherein n_intersect is the number of vertices and edges in A∩

B,

wherein $d^{*}<br><br>\left(A,B\right)=\underset{i\in <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B, and,

wherein $d^{*}<br><br>\left(B,A\right)=\underset{i\in <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i^{\mathrm{\prime <br><br>}}<br><br>}$

where v is a parameter greater than 1 and c′

_i is the number of connected elements in piece i of the difference graph B−

A.

28. An apparatus for using a predetermined model of clustered tasks, for providing help to a user attempting to perform a task, the device comprising:

a) means for logging inputs of the user as steps;

b) means for generating a partial task from the steps logged;

c) means for determining a distance between the partial task generated and each of the clustered tasks;

d) means for determining a minimum of the distances determined; and

e) means for rendering help content to the user, wherein the help content is related to a task cluster associated with the minimum of the distances determined.

29. The apparatus of claim 28 wherein the help content is a script of steps for accomplishing the task.

30. The apparatus of claim 28 wherein the help content is a script of steps for completing the partial task.

31. The apparatus of claim 28 wherein the help content is a query for accomplishing the task.

32. The apparatus of claim 28 wherein the help content is a query for completing the partial task.

33. The apparatus of claim 28 wherein the user input are at least one of a query and a command, and

wherein the means for determining a distance between the partial task generated and each of the clustered tasks include:

i) means for formatting the steps corresponding to the user input as a run time graph having vertices corresponding to the at least one of the query and the command and having edges corresponding to related queries and commands; and

ii) means for determining a distance between the run time graph and graphs of tasks of the task clusters of the model.

34. The apparatus of claim 33 wherein the means for determining distances between the run time graph and the graphs of tasks of the task clusters of the model include:

A) means for determining an intersection of the run time graph and each of the graphs of the tasks of the task clusters of the model;

B) means for determining a difference of the run time graph and each of the graphs of the tasks of the task clusters of the model;

C) means for determining connected elements of each of the differences; and

D) means for determining, in each case, the distance based on the connected elements and the intersection, wherein the distance increases as a number of the connected elements increases.

35. The apparatus of claim 34 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\left(A,B\right)=\underset{i\in <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B.

36. The apparatus of claim 34 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\left(A,B\right)=\frac{\max <br><br>\text{\hspace{1em}<br><br>}\left[d^{*}<br><br>\left(A,B\right),d^{*}<br><br>\left(B,A\right)\right]}{n_{\mathrm{intersect}}}$

wherein n_intersect is the number of vertices and edges in A∩

B,

wherein $d^{*}<br><br>\left(A,B\right)=\underset{i\in <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B, and,

wherein $d^{*}<br><br>\left(B,A\right)=\underset{i\in <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i^{\mathrm{\prime <br><br>}}<br><br>}$

where v is a parameter greater than 1 and c′

₁ is the number of connected elements in piece i of the difference graph B−

A.

37. An apparatus for using a predetermined model of clustered tasks, for providing help to a user attempting to perform a task, the apparatus comprising:

a) means for logging inputs of the user as steps;

b) means for generating a partial task from the steps logged;

c) means for determining a distance between the partial task generated and each of the clustered tasks;

d) means for determining a minimum of the distances determined;

e) means for querying the user whether they want to help; and

f) means for, if the user indicates that they want help, rendering help content to the user, wherein the help content is related to a task cluster associated with the minimum of the distances determined.

38. The apparatus of claim 37 wherein the help content is a script of steps for accomplishing the task.

39. The apparatus of claim 37 wherein the help content is a script of steps for completing the partial task.

40. The apparatus of claim 37 wherein the help content is a query for accomplishing the task.

41. The apparatus of claim 37 wherein the help content is a query for completing the partial task.

42. The apparatus of claim 37 wherein the user input are at least one of a query and a command, and

wherein the means for determining a distance between the partial task generated and each of the clustered tasks include:

i) means for formatting the steps corresponding to the user input as a run time graph having vertices corresponding to the at least one of the query and the command and having edges corresponding to related queries and commands; and

ii) means for determining a distance between the run time graph and graphs of tasks of the task clusters of the model.

43. The apparatus of claim 42 wherein the means for determining distances between the run time graph and the graphs of tasks of the task clusters of the model include:

A) means for determining an intersection of the run time graph and each of the graphs of the tasks of the task clusters of the model;

B) means for determining a difference of the run time graph and each of the graphs of the tasks of the task clusters of the model;

C) means for determining connected elements of each of the differences; and

D) means for determining, in each case, the distance based on the connected elements and the intersection, wherein the distance increases as a number of the connected elements increases.

44. The apparatus of claim 43 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\left(A,B\right)=\underset{i\in <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B.

45. The apparatus of claim 43 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\left(A,B\right)=\frac{\max <br><br>\text{\hspace{1em}<br><br>}\left[d^{*}<br><br>\left(A,B\right),d^{*}<br><br>\left(B,A\right)\right]}{n_{\mathrm{intersect}}}$

wherein n_intersect is the number of vertices and edges in A∩

B,

wherein $d^{*}<br><br>\left(A,B\right)=\underset{i\in <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B, and,

wherein $d^{*}<br><br>\left(B,A\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i^{\mathrm{\prime <br><br>}}<br><br>}$

where v is a parameter greater than 1 and c′

_i is the number of connected elements in piece i of the difference graph B−

A.

46. An apparatus for using a predetermined model of clustered tasks, for providing help to a user attempting to perform a task, the apparatus comprising:

a) means for logging inputs of the user as steps;

b) means for generating a partial task from the steps logged;

c) means for determining a distance between the partial task generated and each of the clustered tasks;

d) means for determining a minimum of the distances determined; and

e) means for, if the minimum of the distances is less than a predetermined threshold, rendering help content to the user, wherein the help content is related to a task cluster associated with the minimum of the distances determined.

47. The apparatus of claim 46 wherein the help content is a script of steps for accomplishing the task.

48. The apparatus of claim 46 wherein the help content is a script of steps for completing the partial task.

49. The apparatus of claim 46 wherein the help content is a query for accomplishing the task.

50. The apparatus of claim 46 wherein the help content is a query for completing the partial task.

51. The apparatus of claim 46 wherein the user input are at least one of a query and a command, and

wherein the means for determining a distance between the partial task generated and each of the clustered tasks include:

i) means for formatting the steps corresponding to the user input as a run time graph having vertices corresponding to the at least one of the query and the command and having edges corresponding to related queries and commands; and

ii) means for determining a distance between the run time graph and graphs of tasks of the task clusters of the model.

52. The apparatus of claim 51 wherein the means for determining distances between the run time graph and the graphs of tasks of the task clusters of the model include:

A) means for determining an intersection of the run time graph and each of the graphs of the tasks of the task clusters of the model;

B) means for determining a difference of the run time graph and each of the graphs of the tasks of the task clusters of the model;

C) means for determining connected elements of each of the differences; and

D) means for determining, in each case, the distance based on the connected elements and the intersection, wherein the distance increases as a number of the connected elements increases.

53. The apparatus of claim 52 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\left(A,B\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B.

54. The apparatus of claim 52 wherein the distance between the run time graph A and each of the graphs B of the tasks of the task clusters of the model, is defined by the expression:

$\mathrm{distance}<br><br>\left(A,B\right)=\frac{\max <br><br>\left[d^{*}<br><br>\left(A,B\right),d^{*}<br><br>\left(B,A\right)\right]}{n_{\mathrm{intersect}}}$

wherein n_intersect is the number of vertices and edges in A∩

B,

wherein $d^{*}<br><br>\left(A,B\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i<br><br>}$

where v is a parameter greater than 1 and c_i is the number of connected elements in piece i of the difference graph A−

B, and,

wherein $d^{*}<br><br>\left(B,A\right)=\underset{i\in <br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{graph}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{pieces}}{\sum <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>v^{<br><br>c_i^{\mathrm{\prime <br><br>}}<br><br>}$

where v is a parameter greater than 1 and c′

_i is the number of connected elements in piece i of the difference graph B−

A.

55. A machine readable medium having machine executable instructions which, when executed by the machine, perform steps for using a predetermined model of clustered tasks to provide help to a user attempting to perform a task, the steps comprising:

a) logging inputs of the user as steps;

b) generating a partial task from the steps logged;

c) determining a distance between the partial task generated and each of the clustered tasks;

d) determining a minimum of the distances determined; and

e) rendering help content to the user, wherein the help content is related to a task cluster associated with the minimum of the distances determined.

56. A machine readable medium having machine executable instructions which, when executed by the machine, perform steps for using a predetermined model of clustered tasks, for providing help to a user attempting to perform a task, the steps comprising:

a) logging inputs of the user as steps;

b) generating a partial task from the steps logged;

c) determining a distance between the partial task generated and each of the clustered tasks;

d) determining a minimum of the distances determined;

e) querying the user whether they want to help; and

f) if the user indicates that they want help, rendering help content to the user, wherein the help content is related to a task cluster associated with the minimum of the distances determined.

57. A machine readable medium having machine executable instructions which, when executed by the machine, perform steps for using a predetermined model of clustered tasks, for providing help to a user attempting to perform a task, the steps comprising:

a) logging inputs cf the user as steps;

b) generating a partial task from the steps logged;

c) determining a distance between the partial task generated and each of the clustered tasks;

d) determining a minimum of the distances determined; and

e) if the minimum of the distances is less than a predetermined threshold, rendering help content to the user, wherein the help content is related to a task cluster associated with the minimum of the distances determined.