BUILDING AND USING PREDICTIVE MODELS OF CURRENT AND FUTURE SURPRISES
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Accused Products
Abstract
Methods are described for identifying events that would be considered surprising by people and identifying how and when to transmit information to a user about situations that they would likely find surprising. Additionally, the methods of identifying surprising situations can be used to build a case library of surprising events, joined with a set of observations before the surprising events occurred. Statistical machine learning methods can be applied with data from the case library to build models that can predict when a user will likely be surprised at future times. One or more models of context-sensitive expectations of people, a view of the current world, and methods for recording streams or events before surprises occur, and for building predictive models from a case library of surprises and such historical observations can be employed. The models of current and future surprises can be coupled with display and alerting machinery.
54 Citations
40 Claims
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1-20. -20. (canceled)
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21. A method of providing user notifications regarding events, the method comprising:
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receiving a first predictive model, wherein the first predictive model is based on a user expectancy model designed to reflect whether a user would predict the event; receiving contextual data that is at least potentially associated with an event; with at least one processor, applying the first predictive model to at least a portion of the contextual data to generate a first prediction for the event; determining that the first prediction differs from a second prediction, the second prediction being based on a second predictive model that is different than the first predictive model; and in response to the determination, selectively outputting an indication regarding the event. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28)
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29. A computer-readable storage device having instructions stored therein, the instructions, when executed on a computing device, cause the computing device to perform operations, the operations comprising:
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receiving contextual data that is at least potentially associated with an event; generating a first prediction for the event based on the received contextual data and on a user expectancy model, wherein the user expectancy model emulates predictive capabilities of a user; determining that the first prediction is different than a second prediction, wherein the second prediction is based on a second model that is different from the user expectancy model; and in response to the determination, selectively outputting an indication regarding the event. - View Dependent Claims (30, 31, 32, 33, 34)
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35. A computing device for providing notifications of events, the computing device comprising:
a memory and a processor that respectively store and execute computer-executable instructions, including instructions that enable the computing device to; receive contextual data that is at least potentially associated with an event; generate a first prediction for the event based on the contextual data and on a user expectancy model, wherein the user expectancy model reflects human predictive capabilities; determine that the first prediction differs from a second prediction, the second prediction being based on a second predictive model that is different than the first predictive model; and in response to the determination, provide an indication regarding the event. - View Dependent Claims (36, 37, 38, 39, 40)
Specification