Presenting a diversity of recommendations
First Claim
1. A computer-implemented method, comprising:
- identifying K results from among a set of data objects, K being an integer greater than 2, wherein identifying K results comprises;
identifying from among the data objects in the set of objects a first result of the K results and first remaining data objects, the first result being one data object of the set of data objects and the first remaining data objects being the set of data objects excluding the first result; and
thenidentifying from among the first remaining data objects a second result of the K results having a maximum conditional interest-likelihood score that a user will select the second result given that the user does not select the first result; and
providing the K results as recommendations to the user including the first result and the second result.
2 Assignments
0 Petitions
Accused Products
Abstract
Methods, systems and apparatus, including computer program products, for providing a diversity of recommendations. According to one method, results are identified so as to increase the likelihood that at least one result will be of interest to a user. Following the identification of a first result, second and later results are identified based on an assumption that the previously identified results are not of interest to the user. The identification of diverse results can be based on formulas that approximate the probability or provide a likelihood score of a user selecting a given result, where a measured similarity between a given object and previously identified results tends to decrease the calculated probability approximation or likelihood score for that object.
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Citations
44 Claims
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1. A computer-implemented method, comprising:
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identifying K results from among a set of data objects, K being an integer greater than 2, wherein identifying K results comprises; identifying from among the data objects in the set of objects a first result of the K results and first remaining data objects, the first result being one data object of the set of data objects and the first remaining data objects being the set of data objects excluding the first result; and
thenidentifying from among the first remaining data objects a second result of the K results having a maximum conditional interest-likelihood score that a user will select the second result given that the user does not select the first result; and providing the K results as recommendations to the user including the first result and the second result. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer-implemented method, for identifying K results from among a set of data objects, where K is an integer greater than 2, the method comprising:
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determining K results from among the set of data objects that give the expression
ITOTAL=I(select R1)+I(select R2 given no selection of R1)+ . . . +I(select RK given no selection of any of R1 . . . RK-1)a maximum value, wherein each Ri is a distinct result in the set of data objects, I(select R1) is a calculated interest-likelihood score representing a likelihood that a user will select R1 from a list of presented results, I(select R2 given no selection of R1) is a calculated interest-likelihood score representing a likelihood that the user will select R2 given that the user does not select R1, and I(select RK given no selection of any of R1 . . . RK-1) is a calculated interest-likelihood score representing a likelihood that the user will select RK given that the user does not select R1 through RK-1; and providing the K results as recommendations to the user. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18)
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14. The computer-implemented method of claim 13, wherein the term I(select R2 given no selection of R1) is an empirically-determined conditional selection probability.
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15. The computer-implemented method of claim 14, wherein the term I(interest in R2 given no selection of R1 is calculated according to the equation
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16. The computer-implemented method of claim 12, wherein the term I(select RK given no selection of any of R1 . . . RK-1) is an empirically determined conditional selection probability.
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17. The computer-implemented method of claim 16, wherein the term I(select RK given no selection of any of R1 . . . RK-1) is calculated according to the equation
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18. The computer-implemented method of claim 11, wherein user selections comprise user clicks.
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19. A system comprising:
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one or more computers programmed to perform operations comprising; identifying K results from among a set of data objects, K being an integer greater than 2, wherein identifying K results comprises; identifying from among the data objects in the set of data objects a first result of the K results and first remaining data objects, the first result being one data object of the set of data objects and the first remaining data objects being the set of data objects excluding the first result; and
thenidentifying from among the first remaining data objects a second result of the K results having a maximum conditional interest-likelihood score that a user will select the second result given that the user does not select the first result; and providing the K results as recommendations to the user including the first result and the second result. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27, 28)
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29. A computer program product, encoded on a computer readable medium, operable to cause data processing apparatus to perform operations to identify K results from among a set of data objects, where K is an integer greater than 2, the operations comprising:
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determining K results from among the set of data objects that give the expression
ITOTAL=I(select R1)+I(select R2 given no selection of R1)+ . . . +I(select RK given no selection of any of R1 . . . RK-1)a maximum value, wherein each Ri is a distinct result in the set of data objects, I(select R1) is a calculated interest-likelihood score representing a likelihood that a user will select R1 from a list of presented results, I(select R2 given no selection of R1) is a calculated interest-likelihood score representing a likelihood that the user will select R2 given that the user does not select R1, and I(select RK given no selection of any of R1 . . . RK-1) is a calculated interest-likelihood score representing a likelihood that the user will select RK given that the user does not select R1 through RK-1; and providing the K results as recommendations to the user. - View Dependent Claims (30, 31, 32, 33, 34, 35, 36)
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32. The computer program product of claim 31, wherein the term I(select R2 given no selection of R1) is an empirically-determined conditional selection probability.
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33. The computer program product of claim 32, wherein the term I(interest in R2 given no selection of R1) is calculated according to the equation
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34. The computer program product of claim 30, wherein the term I(select RK given no selection of any of R1 . . . RK-1) is an empirically determined conditional selection probability.
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35. The computer program product of claim 34, wherein the term I(select RK given no selection of any of R1 . . . RK-1) is calculated according to the equation
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36. The computer program product of claim 29, wherein user selections comprise user clicks.
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37. A system comprising:
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one or more computers programmed to perform operations to identify K results from among a set of data objects, where K is an integer greater than 2, the operations comprising; determining K results from among the set of data objects that give the expression
ITOTAL=I(select R1)+I(select R2 given no selection of R1)+ . . . +I(select RK given no selection of any of R1 . . . RK−
)a maximum value, wherein each Ri is a distinct result in the set of data objects, I(select R1) is a calculated interest-likelihood score representing a likelihood that a user will select R1 from a list of presented results, I(select R2 given no selection of R1) is a calculated interest-likelihood score representing a likelihood that the user will select R2 given that the user does not select R1, and I(select RK given no selection of any of R1 . . . RK-1) is a calculated interest-likelihood score representing a likelihood that the user will select RK given that the user does not select R1 through RK-1; and providing the K results as recommendations to the user. - View Dependent Claims (38, 39, 40, 41, 42, 43, 44)
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40. The system of claim 39, wherein the term I(select R2 given no selection of R1) is an empirically-determined conditional selection probability.
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41. The system of claim 40, wherein the term I(interest in R2 given no selection of R1) is calculated according to the equation
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42. The system of claim 38, wherein the term I(select RK given no selection of any of R1 . . . RK-1) is an empirically determined conditional selection probability.
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43. The system of claim 42, wherein the term I(select RK given no selection of any of R1 . . . RK-1) is calculated according to the equation
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44. The system of claim 37, wherein user selections comprise user clicks.
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Specification