Patent US6330554B1 successfully refreshed from Google Patents.
US6330554B1
Expired / Lapsed
US
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Methods and apparatus using task models for targeting marketing information to computer users based on a task being performed
Assignee: Microsoft Technology Licensing LLC
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Filing: 1999-06-03
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Granted: 2001-12-11
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Expires: 2019-06-03
Abstract
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.
Inventors
- 👤 Steven J. Altschuler
- 👤 David Ingerman
- 👤 Edward K. Jung
- 👤 Greg Ridgeway
- 👤 Lani F. Wu
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-30 16:58
CPC Classifications
G; G06; G06Q; G06Q30/00; G06Q30/02
Claims Analysis
Total Claims: 14
Claim 1
Independent Claim
95 words
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.
Claim 2
Independent Claim
95 words
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.
Claim 3
Dependent Claim
99 words
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.
Claim 4
Dependent Claim
116 words
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: 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.
Claim 5
Dependent Claim
91 words
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: dis tan ce ( A , B ) = ∑ ∈ all graph pieces v c i 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.
Claim 6
Dependent Claim
190 words
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: dis tan ce ( A , B ) = max [ d * ( A , B ) , d * ( B , A ) ] n intersect wherein n intersect is the number of vertices and edges in A∩B, wherein d * ( A , B ) = ∑ ∈ all graph pieces v c i 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 * ( B , A ) = ∑ ∈ all graph pieces v c i ′ 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.
Claim 7
Independent Claim
103 words
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: 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.
Claim 8
Independent Claim
103 words
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: 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.
Claim 9
Dependent Claim
101 words
The apparatus of claim 6 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.
Claim 10
Dependent Claim
122 words
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: 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.
Claim 11
Dependent Claim
91 words
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: dis tan ce ( A , B ) = ∑ ∈ all graph pieces v c i 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.
Claim 12
Dependent Claim
190 words
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: dis tan ce ( A , B ) = max [ d * ( A , B ) , d * ( B , A ) ] n intersect wherein n intersect is the number of vertices and edges in A∩B, wherein d * ( A , B ) = ∑ ∈ all graph pieces v c i 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 * ( B , A ) = ∑ ∈ all graph pieces v c i ′ 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.
Claim 13
Dependent Claim
107 words
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: 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.
Claim 14
Dependent Claim
107 words
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: 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.
References Cited (Backward Citations)
US5551015A
Cited
US5675662A
Cited
US5644723A
Cited
US5687322A
Cited
US5592560A
Cited
US5621812A
Cited
US5638457A
Cited
US5642485A
Cited
US5659469A
Cited
US5448471A
Cited
US5740439A
Cited
US5689703A
Cited
US5581760A
Cited
US5682536A
Cited
US5999908A
Cited
US5511197A
Cited
US5724588A
Cited
US5745764A
Cited
US5710925A
Cited
US5884305A
Cited
US6151585A
Cited
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2004-12-10 | 2005-06-11 | 2005-12-11 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2008-12-10 | 2009-06-11 | 2009-12-11 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2012-12-10 | 2013-06-11 | 2013-12-11 | $7700.00 | Window Closed / Lapsed |