METHODS AND ARCHITECTURE FOR LEARNING AND REASONING IN SUPPORT OF CONTEXT-SENSITIVE REMINDING, INFORMING, AND SERVICE FACILITATION

• US 20080005055A1
• Filed: 06/30/2006
• Published: 01/03/2008
• Est. Priority Date: 06/30/2006
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Horvitz, Eric J.
• Granted Patent: US 7,797,267 B2
• Time in Patent Office: Days
• US Class Current: 706/62
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions

Abstract

Methods and architectures for context-sensitive reminding and service facilitating are disclosed. The architectures monitor user context and activity, senses or infers relevant reminders, goals, such as those that come from a growing need of the user that should be fulfilled, and computes best reminders, and recommend plans on fulfilling need(s) in an optimum way. Statistical models of a user'"'"'s knowledge and recall in different settings may be employed. Facilities, services, and merchants can be identified along a route that the user can take, and cost-benefit analysis is performed for determining which merchant(s) to select to fulfill the need(s). Routes may be created as opportunistic modifications of trips underway. Merchants can respond back with offers of sale to the user for all available needed items, and the user can respond with acceptance or denial of the offers. Merchants can also respond in a bidding fashion in order to gain user'"'"'s patronage.

Claims

1. A computer-implemented system for providing an opportunistic reminder, comprising:

a context component that determines a context of an entity; and

an indication component that employs a probabilistic model to determine whether to provide a reminder to the entity based at least in part upon the context.

2. The system of claim 1, the indication component further comprising a relevance component that reasons about a likelihood of a fact k being relevant to the entity by evaluating a probability that the fact k is relevant given the context, p(relevant(k)|context).

3. The system of claim 1, the indication component further comprising a knowledge component that evaluates whether the entity at least one of knows a fact k and will recall the fact k within a time frame, the knowledge component computes a probability that the entity knows the fact k given the context, p(knows(k)|context).

4. The system of claim 1, the indication component further comprising a valuation component that analyzes a value of the entity at least one of knowing and being reminded of a fact.

5. The system of claim 4, the valuation component evaluates a value of being informed about the fact k by analyzing a difference between a value of knowing versus not knowing k within the context, the valuation component computes Utility(know(k)|context)−

Utility(not know(k)|context).

6. The system of claim 1, the indication component further comprising an integrative component that analyzes an expected value of reminding the entity of a fact.

7. The system of claim 6, the integrative component evaluates a probability that the entity does not know the fact k, given a probabilistic combination of a probability that the fact k is relevant in the context and a probability that the entity would know the fact k, given that the fact k is relevant, p(not know(k)|context)=1=(know(k)|relevant(k), context)*p(relevant(k)|context).

8. The system of claim 6, the integrative component computes the expected value of informing the entity about the fact k in the context under uncertainty, whether the entity knows the fact k or not ahead of time, by evaluating eu(inform(k)|context)=p(not know(k)|context)*[utility(know(k))−

utility(not know(k)|context)]−

cost(interruption(inform(k))|context), where eu is the expected value.

9. The system of claim 1, the indication component employs user specified high-level preferences and goals that define classes of knowledge as being at least one of relevant and having a likelihood above a threshold of being relevant.

10. The system of claim 1, the indication component generates opportunistic reminders related to user knowledge of at least one of a fact, a task desired, a need, and a potential opportunity.

11. The system of claim 1, the indication component evaluates a suspended task and provides the reminder to enable recovery from interruption associated with the suspended task.

12. The system of claim 1, the context being at least one of a location, information associated with a suspended task, a preference, a calendar, a need, a time, a day, a month, an upcoming meeting, a status of expendable resources, and proximal businesses, services, terrain, and recreational facilities.

13. A computer-implemented method of selectively providing opportunistic reminders, comprising:

evaluating a context of a user;

analyzing whether to output a reminder to the user based upon considerations of at least one of relevance, user knowledge, value of the user knowledge, timing and cost of informing the user in view of the context; and

selectively outputting the reminder based upon the analysis.

14. The method of claim 13, evaluating the context further comprises analyzing at least one of a location of the user, a preference of the user, a calendar of the user, a need of the user, a time, a day, a month, a forthcoming meeting, a status of expendable resources, and proximal businesses, services, terrain, and recreational facilities.

15. The method of claim 13, further comprising inferring a likelihood of a fact being relevant to the user.

16. The method of claim 13, further comprising inferring a likelihood that the user at least one of knows about the fact and will recall the fact within a time frame.

17. The method of claim 13, further comprising evaluating a value of the user knowing by way of being reminded about the fact.

18. The method of claim 13, further comprising selectively outputting the reminder based upon explicit and learned goals and preferences of the user.

19. The method of claim 13, further comprising selectively outputting the reminder by maximizing the expected utility associated with the user.

20. A computer-executable system for generating reminders, comprising:

means for determining a context of a user;

means for inferring a first likelihood of a fact being relevant to the user in view of the context;

means for determining a second likelihood that the user at least one of know the fact and will recall the fact within a time frame given the context;

means for analyzing a value of the user knowing the fact by being told given the context;

means for evaluating timing and cost of informing the user in view of the context; and

means for opportunistically outputting the reminder based on one or more of the first likelihood, the second likelihood, the value, the timing, and the cost.