Composable presence and availability services

• US 20040249776A1
• Filed: 06/30/2004
• Published: 12/09/2004
• 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., Apacible, Johnson T., Koch, Paul B.
• Granted Patent: US 7,493,369 B2
• Time in Patent Office: Days
• US Class Current: 706/21
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting

Abstract

The present invention relates to a system and methodology to facilitate collaboration and communications between entities such as between parties to a communication, automated applications and components, and/or combinations thereof. The systems and methods of the present invention include a service that supports collaboration and communication by learning predictive models that provide forecasts of one or more aspects of a user'"'"'s presence and availability. Presence forecasts include a user'"'"'s current location or future locations at different levels of location precision and of the availability to users of different devices or applications. Availability assessments include inferences about the cost of interrupting a user in different ways and a user'"'"'s current or future access to one or more communication channels that may be supported by one or more devices with appropriate capabilities. The predictive models are constructed via statistical learning methods from data collected by considering user activity and proximity from multiple devices, in addition to analysis of the content of users'"'"' calendars, the time of day, and day of week, for example. Beyond ambient data collection, users can provide input via batch input tools or via intermittent probes of their situation and context. Various applications are provided that employ the presence and availability information supplied by the models in order to facilitate collaboration and communications between entities.

Claims

1. A system for determining a user'"'"'s presence and availability, comprising:

a learning component that is trained according to a user'"'"'s pattern of availability with respect to a device, a channel, or a location; and

an interface component that interacts with the learning component to provide presence information for the user in view of the device, the channel or the location.

2. The system of claim 1, the interface component is configured to gather data and perform inferences about the availability of different communication channels, provide presence at different locations, or provide overall availability associated with a current cost of interruption.

3. The system of claim 1, the system of claim 1, the interface component includes configuration tools that allow a system to collect data from users in real time and to perform inference regarding a current and future availability of communication channels, a location of the user, a workload or cost of interruption of users.

4. The system of claim 1, further comprising a monitor component to monitor ambient data and capture user tags on data.

5. The system of claim 4, the monitor component acquires information from users, in one-shot assessment settings or by performing in-stream, assessment via experience sampling.

6. The system of claim 5, the experience sampling includes probing users for their states or context at different times or probing users regarding how busy they currently are at random times within intervals determined by user preferences.

7. The system of claim 1, the interface component provides configuration option for devices having one or more communications channels including a time setting for communications availability.

8. The system of claim 1, the interface component includes options to configure user permissions and setting interruption costs.

9. The system of claim 1, the interface component includes configuration options to configure at least one location within at least one other location.

10. The system of claim 1, further comprising a wireless component or a global positioning component for automatically determining a location.

11. The system of claim 1, the interface component includes options for configuring explicit channels of communication.

12. The system of claim 11, the channels of communications provide distinctions for learning and reasoning to occur for use in coordinating and routing communications and collaboration.

13. The system of claim 11, further comprising a data collection component relating to availabilities of the channels over time and a forecast component that is created on demand of users or agents that use availability forecasts.

14. The system of claim 13, the channels are input to systems in an organization by default, or a base list of standard channels are included that are extended by users or administrators.

15. The system of claim 1, the interface component enables users with privileges to view inferences in terms of high-level summaries as displayed, or via, drill down, into more specific views on probability distributions.

16. The system of claim 15, the probability distributions are associated with an adjustment to control the prediction accuracy of a system.

17. The system of claim 15, the interface component provides at least one of a maximum likelihood time that channels will become available, an expected cost of interruption in terms of a range for a bar graph between the minimum and maximum cost specified by a user, a current computed expected value, a summary of where the user was last seen as active on a device being monitored by the system, and an age of a current inference.

18. The system of claim 15, further comprising a details selection in order that a user with privileges can view details of an inferred probability distribution.

19. The system of claim 18, the probability distribution includes a base probability distribution and a cumulative probability distribution.

20. The system of claim 15, further comprising an expected cost indication associated with a willingness to pay to avoid an interruption at a current time.

21. The system of claim 15, further comprising a probability distribution over high and low workloads being inferred about a user'"'"'s busy-ness state.

22. The system of claim 21, further comprising probabilities used in conjunction with costs assessed on a respective state to compute an expected cost of interruption, as Σ

_ip(S_i|E₁ . . . E_n)Cost (S_iA_j), where p(S_i|E₁ . . . E_n) are the probabilities of each state of interruptability S_i, given observations E₁ . . . E_n and where Cost (S_i, A_j) represents the cost associated with being interrupted in the state by alert type A_j.

23. A schema to facilitate communications and collaboration between entities relating to a user'"'"'s presence and availability, comprising:

at least a first data field associated with a device parameter, a channel parameter, and a location parameter; and

a second data field that binds the parameters in order to facilitate determination of a user'"'"'s presence and availability.

24. The schema of claim 23, the data fields are associated with at least one method for communications, the methods include methods to allow for querying about time until use of device or availability of a channel, methods to allow for querying about user presence:

current and expected time of availability, methods to query for a user'"'"'s Cost of Interruption (COI) or methods to query for a user'"'"'s current available channels.

25. The schema of claim 23, the first data field associated with models that include Graph data, Sensing data, Location data, data relating to which application appears on Top, Keyboard data, Remote connection, Meeting data, and communications interface data.

26. The schema of claim 23, further comprising user preference data.

27. The schema of claim 23, further comprising a Users table having a UserId, an Alias, or a UserName field.

28. The schema of claim 23, further comprising a Computers table having a ComputerId, or a ComputerName field.

29. The schema of claim 23, further comprising a Locations table having a LocationId, a UserId, a ParentLocationId, or a LocationName field.

30. The schema of claim 23, further comprising a Devices table having a DeviceId, a UserId, a ComputerId, a LocationId, or a DeviceName field.

31. The schema of claim 23, further comprising a DeviceAvailability table having a DeviceId, a StartTimeTicks, or an EndTimeTicks field.

32. The schema of claim 23, further comprising a Bindings table having a BindingId or a BindingName field.

33. The schema of claim 32, the Bindings table associated with at least one of a user'"'"'s Presence, Email, Remote Presence, and Presence and Connected status.

34. The schema of claim 23, further comprising a Channels table having a ChannelId, a UserId, a BindingId, or a ChannelName field.

35. The schema of claim 34, the Channels table associated with at least one of a user'"'"'s IM (Instant Message), Email, Full screen, Video, Audio, and Phone status.

36. The schema of claim 23, further comprising a Device Channels table having a DeviceId, or a ChannelId.

37. The schema of claim 23, further comprising a Wireless Access table having a UserId, a WirelessAccessPoint, or a LocationId field.

38. The schema of claim 23, further comprising an Activity Types table having an ActivityTypeId, or an ActivityTypeName.

39. The schema of claim 23, the Activity type table associated with at least one of a Top application, a Location, an application running, an Audio, a Remote status, a Present status, and a Connected status.

40. The schema of claim 23, further comprising a Computer Activity Log table having a UserId, a ComputerID, an ActivityTypeId, an EndTimeTicks, a StartTimeTicks, or Property field.

41. The schema of claim 23, further comprising a Meetings table having a UserId, a StartTimeTicks, a MeetingId, an Attended Meeting, a Landmark, an Interruptability, an Actual Location, a Subject, a Location, an Organizer, a Required Attendees, an Optional Attendees, a Meeting Sender, a Meeting Resources, an EntryId, a Busy Status, a Label, an Importance, a Response Status, a Recurrence Pattern, a Minutes Duration, a Minutes Reminder, an IsResponseRequested, an IsOnlineMeeting, an IsPatternException a MyName, a MyOfficeLocation, a MyOwnedAliases, a MyAliases, a MyManagersManager, a MyManager, or a MyDirectReports field.

42. A computer readable medium having computer readable instructions stored thereon for implementing the schema of claim 23.

43. A method to provide presence and availability forecasts, comprising:

determining a presence model to predict a user'"'"'s presence and availability with respect to a device; and

determining parameters in accordance with the model, the parameters relating to at least one of a device, a channel of communication, and a location in order to predict the user'"'"'s presence and availability.

44. A system to facilitate communications and collaboration between entities, comprising:

means for learning availability patterns from at least one of a device variable, a channel variable, and a location variable;

means for generating predictions relating to future availability patterns based upon the variable; and

means for distributing the availability patterns to at least one user.

45. A graphical user interface to facilitate presence and availability forecasting comprising:

a display object associated with configuring parameters relating to a user'"'"'s location, channels of communications, and devices;

at least one input to configure the parameters; and

a component to transmit status with respect to the parameters, the status relating to a user'"'"'s presence and availability.

46. The graphical user interface of claim 45, further comprising a hierarchy for configuring and displaying locations.

47. The graphical user interface of claim 45, further comprising a component for configuring a location within a location.

48. The graphical user interface of claim 45, further comprising a component for configuring wireless access points.

49. The graphical user interface of claim 45, further comprising a component for defining a user'"'"'s definition of presence.

50. The graphical user interface of claim 45, further comprising a component for defining a fixed or dynamic location.

51. The graphical user interface of claim 45, further comprising an electronic calendar component for defining a user'"'"'s availability with respect to a device.

52. The graphical user interface of claim 45, further comprising a prediction component for sharing a user'"'"'s availability status with respect to a device, a channel, or a location.

53. The graphical user interface of claim 45, the prediction component further comprising an adjustable probability threshold setting.

54. The graphical user interface of claim 45, further comprising an output to display cost of interruption levels.

55. The graphical user interface of claim 45, further comprising input options to vary the cost of interruption levels.

56. The graphical user interface of claim 55, the cost of interruption levels are associated with different types of communications interruptions.

57. The graphical user interface of claim 56, different types of communications interruptions include at least one of a real-time call, a visual alert, and an audiovisual alert.

58. The graphical user interface of claim 45, a component to provide cost of interrupt assessments in accordance with alert types or provide a review of costs of different types of alerts at different states of interruptability.

59. A method for processing models, comprising:

selecting at least one existing model from a plurality of models, the existing model built for at least one user; and

extending the existing model for a subsequent user in view of data from the subsequent user.

60. The method of claim 59, further comprising adding personalized data to a training set collected from one or more users, and gradually replacing the data by new personalized experience data.

61. The method of claim 59, further comprising employing a model mixture for inference.

62. The method of claim 61, further comprising determining an interruptability filter that provides a probability that a user is in a high cost of interruption state versus a low cost of interruption state given a set of observations.

63. The method of claim 61, the interruptability filter includes a weighting parameter, k, that ranges between 0 and 1 to integrate a probability that a user is in a high cost of interruption state from at least two models.

64. The method of claim 63, further comprising the following equation:

p(interruptability=high cost|observations)=(1−

k)*p(interruptability=high cost|observations, generic model)+k*p(interruptability=high cost|observations, personal model)

where k is set as a function of a measure of competency k-ƒ

(competency) where competency is determined from the performance of a personal model on cases held out for testing.

65. A method for processing presence and availability schema, comprising:

automatically processing a schema by composing the schema into sets of higher-level features;

processing combinations of the features, the combinations built from boolean statements from at least two features; and

processing predicates relating to durations, temporal patterns of activity, and persistence in accordance with the schema.

66. The method of claim 65, further comprising determining higher-level features via search, clustering, or provided as handcrafted definitions.

67. The method of claim 65, the features include at least one of time of day, day of week, weekend, current application, time current application, previous application, time previous application, application switches, application title information, user presence information, user activity information, computer or device information, location information, wireless information, user role information, user organization information, and user colleague information.