Decision-theoretic approach to harnessing text classification for guiding automated action
First Claim
1. A computer-implemented method comprising:
- determining a text to analyze;
determining an action probability based on at least one of the text and contextual information;
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.
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Accused Products
Abstract
A decision-theoretic approach for guiding automated actions. In one embodiment, a computer-implemented method first determines a text to analyze. The method then determines an action probability based on the text. Words and phrases as well as information in special fields, such as distinctions and patterns in the header of email, observations about recent user activity, and organizational information are considered in classification. Based on the inferred probability that a user has a goal under consideration, the method selects one of the following options: (1) inaction, (2) automatic action, or (3) suggested action with user approval. Upon the method selecting either the (1) automatic action option or the (2) suggested action with user approval option—the latter also in conjunction with receiving actual user approval—the method performs an action based on the text.
105 Citations
46 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 at least one of the text and contextual information;
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)
performing a feature-selection phase; and
,performing a model-construction phase based on the feature-selection phase.
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8. The method of claim 7, 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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9. The method of claim 7, wherein performing a feature-selection phase comprises seeding the feature-selection phase with domain-specific knowledge.
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10. 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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11. The method of claim 10, 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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12. The method of claim 11, wherein utilizing decision theory comprises utilizing cost/benefit analysis.
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13. The method of claim 12, wherein utilizing cost/benefit analysis comprises utilizing the cost/benefit analysis in a contextual manner.
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14. 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 (15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
performing a feature-selection phase; and
,performing a model-construction phase based on the feature-selection phase.
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20. The medium of claim 19, 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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21. The medium of claim 19, wherein performing a feature-selection phase comprises seeding the feature-selection phase with domain-specific knowledge.
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22. The medium of claim 14, 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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23. The medium of claim 22, 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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24. The medium of claim 23, wherein utilizing decision theory comprises utilizing cost/benefit analysis.
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25. The medium of claim 24, wherein utilizing cost/benefit analysis comprises utilizing the cost/benefit analysis in a contextual manner.
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26. 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 (27, 28, 29, 30)
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31. A system that facilitates automated computer action, comprising:
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a component that receives information related to intentions of a user; and
an action direction component that analyzes the information and makes a probabilistic determination as to a user desired action to be taken in connection with the received information. - View Dependent Claims (32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45)
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46. A system that facilitates automated computer action, comprising:
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means for analyzing content related to intentions of a user; and
means for making a probabilistic determination as to a user desired action to be taken in connection with the analyzed content.
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Specification