Combining predictive models of forgetting, relevance, and cost of interruption to guide automated reminding
First Claim
1. A system implemented on a machine that develops or utilizes predictive models of human memory to effectuate or facilitate automated reminding, comprising:
- a component that acquires an event or other item via an interface, the component evaluates the event or other item for relevance based at least in part on a predictive model for the relevance of the event or other item based on contextual information or attributes associated with the event or other item, the component also infers a probability of the user forgetting about the event or other item, combines the probability of the user forgetting about the event or other item with a user specific cost of forgetting to ascertain an expected cost for not being reminded, the component compares the expected cost for not being reminded with an expected cost for interrupting the user, based at least in part on the comparison between the expected cost for being reminded and the expected cost for interrupting the user the component generates and delivers a reminder notification to the user.
2 Assignments
0 Petitions
Accused Products
Abstract
The claimed matter provides systems and/or techniques that develop or use predictive models of human forgetting to effectuate automated reminding. The system includes the use of predictive models that infer the probability that aspects of items will be forgotten, models that evaluate the relevance of recalling aspects of items in different settings, based on contextual information related to user attributes associated with the items, and models of the context-sensitive cost of interrupting users with reminders. The system can combine the probability of users forgetting aspects of an item with an assessed cost of forgetting those aspects to ascertain expected costs for not being reminded about events, compare expected costs for not being reminded with expected costs for interrupting users, and based on comparisons between expected costs for being reminded and expected costs for interrupting users regarding events, generate and deliver reminder notifications to users about items.
-
Citations
20 Claims
-
1. A system implemented on a machine that develops or utilizes predictive models of human memory to effectuate or facilitate automated reminding, comprising:
a component that acquires an event or other item via an interface, the component evaluates the event or other item for relevance based at least in part on a predictive model for the relevance of the event or other item based on contextual information or attributes associated with the event or other item, the component also infers a probability of the user forgetting about the event or other item, combines the probability of the user forgetting about the event or other item with a user specific cost of forgetting to ascertain an expected cost for not being reminded, the component compares the expected cost for not being reminded with an expected cost for interrupting the user, based at least in part on the comparison between the expected cost for being reminded and the expected cost for interrupting the user the component generates and delivers a reminder notification to the user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
-
13. A machine implemented method that develops or utilizes predictive models of human forgetting and/or remembering to effectuate or facilitate automated reminding, comprising:
-
evaluating an item for relevance based on a user assessment of the item, contextual information associated with the user, or attributes associated with the item; predicting a probability of the user forgetting about the item; aggregating the probability of the user forgetting about the item with a user specific cost to ascertain a cost for not being reminded about the item; contrasting the cost for not being reminded about the item with a cost for interrupting the user about the item; and based at least in part on the contrasting, disseminating a reminder notification about the item to the user. - View Dependent Claims (14, 15, 16, 17)
-
-
18. A system that utilizes predictive models of human memory to effectuate automated reminding, comprising:
-
means for assessing an event for relevance based on a user assessment of the item, contextual information associated with the user, or attributes associated with the item; means for inferring a probability of the user forgetting about one or more aspects of the item; means for combining the probability of the user forgetting about the item with a user specific cost to ascertain a cost for not being reminded about one or more aspects of the item; means for contrasting the cost for not being reminded about one or more aspects of the item with a cost for interrupting the user about the event; and means for disseminating a reminder notification about the event to the user. - View Dependent Claims (19, 20)
-
Specification