Microsoft Technology Licensing, LLC

David O Hovel

Carl Myers Kadie

Eric J Horvitz

Andrew W Jacobs

David Earl Heckerman

Eric I Horvitz

John S Breese

Adrian C Klein

Samuel D Hobson

Gregory L Shaw

Jacobus A Rommelse

Bryan M Willman

John D Vert

Robert I Davidson

Russell P Blake

Rita Mang Chee Wong

Dan Alvin Hinsley

The present invention relates to a system () and methodology () to enable a plurality of information associated with electronic messages, for example, to be automatically prioritized by a priorities system () for transmittal to a user or system. The priorities system () can employ classifiers () that can be explicitly and/or implicitly trained to prioritize one or more received messages () according to a learned importance to the user. As an example, messages () can be classified as high, medium, low or other degrees of importance via a training set of examples () or types of messages having similar degrees of importance. A background monitor () can be provided to monitor a user's activities regarding message processing to further refine or tune the classifier () according to the user's personal decisions relating to message importance. Other priorities classifications can involve determinations relating to a loss associated with a time for delayed review or processing of the message.

Priorities generation and management

The present invention relates to a system and methodology to enable a variety of information associated with one or more notification sources to be directed to one or more notification sinks via a notification platform architecture. The architecture includes a context analyzer for determining a user's state such as location and attentional focus, wherein the user's state is employed by a notification manager to make decisions regarding what, when and how information generated by the notification sources should be forwarded to the notification sinks, for example. These decisions can include a cost benefit analysis wherein considerations are given as to whether the benefits of notifying the user are outweighed by the costs of disrupting the user. Decision-theoretic policies and/or somewhat less formal heuristic policies can be employed to enable the decision-making process within the notification manager.

Notification platform architecture

An architecture for a notification platform is disclosed. In one embodiment, the architecture includes a user mechanism, one or more notification sources and sinks, and a notification manager. The user mechanism stores information regarding notification parameters of a user, such as the user's default notification preferences, and may also contain, access, and/or infer contextual information. Each notification source generates notifications intended for the user, while each notification sink can provide the notifications to the user. Notification sources and sinks provide information via standardized notification schema. The notification manager is designed to appropriately convey the notifications generated by the sources to the sinks, based on information provided by the user mechanism, and by the sources and sinks. As disclosed, the architecture is applicable to entities other users as well.

The present invention relates to a system () and methodology () to enable a variety of information associated with one or more notification sources (-) to be directed to one or more notification sinks (-) via a notification platform architecture (). The architecture () includes a context analyzer () for determining a user's state such as location and attentional focus, wherein the user's state is employed by a notification manager () to make decisions regarding what, when and how information generated by the notification sources (-) should be forwarded to the notification sinks (-), for example. These decisions can include a cost benefit analysis wherein considerations are given as to whether the benefits of notifying the user are outweighed by the costs of disrupting the user. Decision-theoretic policies () and/or somewhat less formal heuristic policies () can be employed to enable the decision-making process within the notification manager ().

Determination of the current context of the user, such as the user's current location and attentional state, is disclosed. The determined context can be used to assist determination as to whether, when and how notifications intended for the user should be conveyed to him or her. In varying embodiments of the invention, the context is determined via one or more of: direct specification by the user; direct measurement using one or more sensors; a user-modifiable profile indicating context; one or more potentially user-modifiable rules that indicate context; and, and inferential analysis utilizing a model, such as a Bayesian network or other statistical model.

Contextual models and methods for inferring attention and location

A method and system provides for booting a computer system after configuration data becomes unusable. One method and system provides for booting the computer system from a set of configuration data that last booted the system properly. An embodiment is directed to attempting to boot the computer system from a first set of configuration data, and, if the attempt is unsuccessful, automatically booting the computer system using the second set of configuration data which successfully booted the computer system and was previously stored. In response to a successful boot of the computer system using the first set of configuration data, an embodiment is directed to updating second set of configuration data so that it is equivalent to the first set of configuration data as the second set of configuration data that successfully booted the computer system.

Booting a computer system using a last known good set of configuration data

Performance of a decision-theoretic analysis to determine which notifications as can be received from notification sources should be conveyed to the user, and via which modes of which notification sinks, is disclosed. A value can be determined for each mode of each notification sink, equal to an expected value of information contained within the notification, minus an expected cost of disruption to convey the notification via each mode of each sink, minus an expected value of the user independently learning the information contained with the notification without notification, and minus an actual cost of conveying the notification via each mode of each sink. If this value is greater than a predetermined conveyance threshold for any mode of any sink, then the notification is conveyed via the mode of the sink having the highest such value.

Decision theoretic principles and policies for notification

An intelligent user assistance system is disclosed. The system is constructed using a reasoning model to determine the probability of a user's intentions, goals, or informational needs in the context of a software program. This is accomplished through analysis of information about the user's actions, the program state, and spoken words. The system monitors user interaction with the software program and applies probabilistic reasoning to sense that the user may need assistance in using a particular feature or to accomplish a specific task. The inference system accesses a thorough and updateable user profile system to continually check for competencies and changes assistance that is given based on the competencies.

Intelligent user assistance facility

A general event composing and monitoring system that allows high-level events to be created from combinations of low-level events. An event specification tool allows for rapid development of a general event processor that creates high-level events from combinations of user actions. The event system, in combination with a reasoning system, is able to monitor and perform inference about several classes of events for a variety of purposes. The various classes of events include the current context, the state of key data structures in a program, general sequences of user inputs, including actions with a mouse-controlled cursor while interacting with a graphical user interface, words typed in free-text queries for assistance, visual information about users, such as gaze and gesture information, and speech information. Additionally, a method is provided for building an intelligent user interface system by constructing a reasoning model to compute the probability of alternative user's intentions, goals, or informational needs through analysis of information about a user's actions, program state, and words. The intelligent user interface system monitors user interaction with a software application and applies probabilistic reasoning to sense that the user may need assistance in using a particular feature or to accomplish a specific task. The intelligent user interface also accepts a free-text query from the user asking for help and combines the inference analysis of user actions and program state with an inference analysis of the free-text query. The inference system accesses a rich, updatable user profile system to continually check for competencies and changes assistance that is given based on user competence.

Intelligent user assistance facility for a software program

A system and method for determining a workload placed on a target computer system during execution of a specified computer program. The system receives a set of performance measurements representing the performance of the target computer system during execution of the specified computer program. The system then identifies a plurality of workloads and for each identified workload, uses a model of the target computer system to predict a set of performance measurements that would results when a computer program that places the identified workload on the target computer system is executed. The system selects the identified workload whose set of predicted performance measurements most closely matches the received set of performance measurements as the determined workload that was place on the target computer system during execution of the specified computer program. The system uses the selected workload to predict the performance of the specified computer program on the target computer system with various different configurations. The system also determines the resource that is a bottleneck for each of the different configurations.

Automatic bottleneck detection by means of workload reconstruction from

An event composing and monitoring system that allows high-level events to be created from combinations of low-level events. An event specification tool, contained in the system, allows for rapidly developing a general event processor that creates high-level events from combinations of user actions. An event system, in combination with an inference system, monitors and infers, for various purposes, about several classes of events including: current program context; state of key data structures; user input sequences, including actions with a mouse-controlled cursor while interacting with a graphical user interface; words typed in free-text help queries; visual user information, such as gaze and gesture information; and user speech information. Additionally, an intelligent user interface is provided by constructing a reasoning model that computes probability of alternative user intentions, goals or information needs through analyzing information regarding program state, and that user's actions and free-text query words. Specifically, the interface monitors user interaction with a program and probabilistically reasons to sense that a user may need assistance in using a particular feature or to accomplish a specific task. This interface accepts a free-text help query from the user and combines the inference analysis of user actions and the program state with an inference analysis of the query. The inference system, using an updateable user profile, continually checks for user competencies and, based on such competencies, changes assistance that is offered.

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Bellevue, WA, United States of America

David O Hovel