Methods and apparatus using task models for targeting marketing information to computer users based on a task being performed
First Claim
1. A method for using a predetermined model of clustered tasks, for providing marketing information 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 marketing information content to the user, wherein the marketing information content is related to a task cluster associated with the minimum of the distances determined.
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Accused Products
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.
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Citations
11 Claims
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1. A method for using a predetermined model of clustered tasks, for providing marketing information to a user attempting to perform a task, the method comprising steps of:
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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 marketing information content to the user, wherein the marketing information content is related to a task cluster associated with the minimum of the distances determined. - View Dependent Claims (2, 3, 4, 5)
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.
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3. The method of claim 2 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:
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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.
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4. The method of claim 3 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:
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where v is a parameter greater than 1 and ci is the number of connected elements in piece i of the difference graph A−
B.
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5. The method of claim 3 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:
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wherein nintersect is the number of vertices and edges in A∩
B,wherein where v is a parameter greater than 1 and ci is the number of connected elements in piece i of the difference graph A−
B, and,wherein 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.
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6. An apparatus for using a predetermined model of clustered tasks, for providing marketing information to a user attempting to perform a task, the apparatus comprising:
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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 marketing information content to the user, wherein the marketing information content is related to a task cluster associated with the minimum of the distances determined. - View Dependent Claims (7, 8, 9, 10)
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.
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8. The apparatus of claim 7 wherein the means for determining distances between the run time graph and the graphs of tasks of the task clusters of the model include:
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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.
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9. The apparatus of claim 8 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:
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where v is a parameter greater than 1 and ci is the number of connected elements in piece i of the difference graph A−
B.
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10. The apparatus of claim 8 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:
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wherein nintersect is the number of vertices and edges in A∩
B,wherein where v is a parameter greater than 1 and ci is the number of connected elements in piece i of the difference graph A−
B, and,wherein 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.
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11. 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 marketing information to a user attempting to perform a task, the steps comprising:
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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 marketing information content to the user, wherein the marketing information content is related to a task cluster associated with the minimum of the distances determined.
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Specification