Methods for and applications of learning and inferring the periods of time until people are available or unavailable for different forms of communication, collaboration, and information access

• US 7,519,676 B2
• Filed: 01/31/2005
• Issued: 04/14/2009
• Est. Priority Date: 06/28/2001
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Horvitz, Eric J., Jacobs, Andrew W., Kadie, Carl M.
• Primary Examiner(s): Dalencourt; Yves
• Application Number:
  US11/047,210
• Publication Number:
  US 20050132005A1
• Time in Patent Office: 1,534 Days
• Field of Search: 709/200, 709/11, 709/46, 709/45
• US Class Current: 709/207
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting

Abstract

A system and method are provided to learn and infer the time until a user will be available for communications, collaboration, or information access, given evidence about such observations as time of day, calendar, location, presence, and activity. The methods can be harnessed to coordinate communications between parties via particular modalities of interaction. The system includes a user state identifier that determines a user'"'"'s state from background knowledge, the flow of time, or one or more context information sources. A data log can be employed to store information about user state changes and observational evidence to accumulate statistics and build inferential models of the availability and unavailability of users for different kinds of communication, collaboration, and information access. A forecaster is constructed from the accumulated statistics and/or learned models to enable a determination of a user'"'"'s likely return, or, more generally, the probability distribution over a user'"'"'s likely return to particular states of availability. The forecaster can be employed to cache information for offline access, drive displays of availability and unavailability, to send messages that include availability forecasts, and to automatically perform scheduling or rescheduling of communications.

Claims

1. An information transfer system, comprising a processor and a computer readable storage medium having stored thereon the following components:

a predictive component to estimate when a user will likely be in a setting have access to a messaging system to review one or more messages; and

an answering component to automatically provide an adaptive message reply in association with the predictive component relating to when the user is likely to have access to the messaging system to review the one or more messages wherein the adaptive message reply includes dynamically computed user availability status comprising a confidence measure that the user will return in an expected timeframe, the dynamically computed user availability status, includes a forecast of an expected time for at least one of until the user will likely review the messages, be available to review the messages, or be in a particular situation wherein the expected time is computed as a sum of times, weighted by different likelihoods of expected time of return and the confidence measure is updated over time as new information is received from one or more context information sources.

2. The system of claim 1, the estimate further comprising at least one of when the messages will likely be unseen for some amount of time.

3. The system of claim 2, wherein the messages are at least of some urgency, and the messages are from one or more people of particular importance to the user.

4. The system of claim 1, further comprising at least one of a determination of the time until a user reviews different kinds of information based on review histories, and the time until the user will be in one or more types of settings.

5. The system of claim 4, each of the settings associated with one or more types of communications.

6. The system of claim 1, further comprising a notification component that alerts the user to the one or more received messages based on information regarding the access to a messaging system by the user when the one or more messages are received in a form that is difficult for the user to review in a current context.

7. The system of claim 1, wherein the user availability status comprises an expected time of return computed as a sum of times, weighted by different likelihoods of expected time of return.

8. The system of claim 7, wherein the confidence measure is updated over time as new information is received from one or more context information sources.

9. A hand-assessed communications system to provide information, comprising:

a processor; and

a computer readable storage medium having stored thereon the following components;

an availability profile configurable by a user indicating the user'"'"'s availability for different types of activities; and

a supplementary component to automatically indicate in the availability profile periods of availability and unavailability based on forecasting information; and

a communications component that provides the availability profile to one or more other users to facilitate at least one of communications, collaboration, or coordination between the user and the one or more other users wherein the availability profile comprises a confidence measure updated via one or more series of statements generated about an expected time until a user is available with respective confidences, wherein the expected time is computed as a sum of times, weighted by different likelihoods of expected time of return and the respective confidences are updated over time as new information is received from one or more context information sources.

10. The system of claim 9, the availability profile indicated on at least one of a form or a calendar-like representation.

11. The system of claim 9, the availability profile is conditioned on one or more variables.

12. The system of claim 11, the one or more variables including at least one of a time of day, an appointment status, a meeting type, or a sensed activity.

13. The system of claim 9, further comprising one or more hand-assessed models that are refined through data collection and learning.

14. The system of claim 9, further comprising a user tracking component that blocks out a calendar associated with the user ahead of time to allow the user to return from a meeting based on an appointment time and an ending time of the meeting.

15. The system of claim 14, wherein the user tracking component negotiates a better time with one or more other users who send requests for meetings that are near one or more other meetings by providing information that the user is likely to be in transit from the other meetings.

16. A system for inferring user availability comprising:

a data store tat stores information collected from one or more context information sources regarding activity associated with a user; and

a processor executing the following components;

a user state identifier component that detects a change in a user state from the context information sources and updates the data store;

a forecasting component that builds a prediction model from the information in the data store and forecasts likely future return or likely future unavailability of the user; and

a communication component that automatically transmits at least a reply comprising a time of the likely future return of the user with respective confidences to contactors sending messages to the user and further updates the time of likely future return of the user through a series of statements transmitted to the contactors, the series of statements update the confidences over time as new information is received from the context information sources, wherein the time of likely future return is computed as a sum of times, weighted by different likelihoods of expected time of return.