Learning by observing a user's activity for enhancing the provision of automated services
First Claim
1. A computer-implemented method comprising:
- determining a text to analyze;
determining an action probability based on the text;
selecting an option selected from the group essentially consisting of;
(1) inaction, (2) automatic action, and (3) suggested action with user approval, based on the action probability; and
, upon selecting the option comprising one of the (1) automatic action and the (2) suggested action with user approval, the latter also in conjunction with receiving actual user approval, performing an action based on the text.
2 Assignments
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Accused Products
Abstract
Learning by observing a user'"'"'s activity for enhancing the provision of automated services. In one embodiment, a computer-implemented method first determines a text to analyze. The method then determines the probabilities of a user'"'"'s goals associated with the text based on features observed in the text, related materials, or user actions, and based on the probabilities of a user'"'"'s goals, selects one of the following options: (1) inaction, (2) automatic action, or (3) dialog with users about potential actions to seek a user'"'"'s approval. Upon the method selecting either the (1) automatic action option or the (2) dialog with user about suggested action—the latter also in conjunction with receiving actual user approval—the method performs an action based on the text. In one embodiment, the method waits a predetermined time prior to action, determined by performing a statistical regression as to the predetermined time that should be waited based on a length of each text. Furthermore, in one embodiment the action probability is determined by a text classification system, such that the system is continually trained based on each text inputted thereinto.
60 Citations
41 Claims
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1. A computer-implemented method comprising:
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determining a text to analyze;
determining an action probability based on the text;
selecting an option selected from the group essentially consisting of;
(1) inaction, (2) automatic action, and (3) suggested action with user approval, based on the action probability; and
,upon selecting the option comprising one of the (1) automatic action and the (2) suggested action with user approval, the latter also in conjunction with receiving actual user approval, performing an action based on the text. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
performing a feature-selection phase; and
,performing a model-construction phase based on the feature-selection phase.
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11. The method of claim 10, wherein performing a feature-selecting phase comprises training the text classification system by inputting a plurality of texts based on which action is to occur and inputting a plurality of texts based on which action is not to occur.
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12. The method of claim 10, wherein performing a feature-selection phase comprises seeding the feature-selection phase with domain-specific knowledge.
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13. The method of claim 1, wherein selecting an option comprises:
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associating a boundary between the (1) and the (2) options with a first probability threshold, and a boundary between the (2) and the (3) options with a second probability threshold;
upon determining that the action probability is less than the first probability threshold, selecting the (1) option;
upon determining that the action probability is greater than the second probability threshold, selecting the (3) option; and
,otherwise, selecting the (2) option.
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14. The method of claim 13, wherein associating a boundary between the (1) and the (2) options with a first probability threshold, and a boundary between the (2) and the (3) options with a second probability threshold comprises utilizing decision theory to determine the first and the second probability thresholds.
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15. The method of claim 14, wherein utilizing decision theory comprises utilizing cost/benefit analysis.
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16. The method of claim 15, wherein utilizing cost/benefit analysis comprises utilizing the cost/benefit analysis in a contextual manner.
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17. A machine-readable medium having processor instructions stored thereon for execution by a processor to cause performance of a method comprising:
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determining a text to analyze;
determining an action probability based on the text;
selecting an option selected from the group essentially consisting of;
(1) inaction, (2) automatic action, and (3) suggested action with user approval, based on the action probability; and
,upon selecting the option comprising one of the (1) automatic action and the (2) suggested action with user approval, the latter also in conjunction with receiving actual user approval, performing an action based on the text. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33)
performing a feature-selection phase; and
,performing a model-construction phase based on the feature-selection phase.
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28. The medium of claim 27, wherein performing a feature-selecting phase comprises training the text classification system by inputting a plurality of texts based on which action is to occur and inputting a plurality of texts based on which action is not to occur.
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29. The medium of claim 27, wherein performing a feature-selection phase comprises seeding the feature-selection phase with domain-specific knowledge.
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30. The medium of claim 17, wherein selecting an option comprises:
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associating a boundary between the (1) and the (2) options with a first probability threshold, and a boundary between the (2) and the (3) options with a second probability threshold;
upon determining that the action probability is less than the first probability threshold, selecting the (1) option;
upon determining that the action probability is greater than the second probability threshold, selecting the (3) option; and
,otherwise, selecting the (2) option.
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31. The medium of claim 30, wherein associating a boundary between the (1) and the (2) options with a first probability threshold, and a boundary between the (2) and the (3) options with a second probability threshold comprises utilizing decision theory to determine the first and the second probability thresholds.
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32. The medium of claim 31, wherein utilizing decision theory comprises utilizing cost/benefit analysis.
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33. The medium of claim 32, wherein utilizing cost/benefit analysis comprises utilizing the cost/benefit analysis in a contextual manner.
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34. A computerized system comprising:
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a program in which a user is able to perform an action; and
,an action direction program to determine an action probability based on an input;
select an option selected from the group essentially consisting of;
(1) inaction, (2) automatic action, and (3) suggested action with user approval, based on the action probability; and
, upon selecting the option comprising one of the (1) automatic action and the (2) suggested action with user approval, the latter also in conjunction with receiving actual user approval, performing an action within the program based on the input.- View Dependent Claims (35, 36, 37, 38, 39, 40, 41)
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Specification