Microsoft Technology Licensing, LLC

Other

Andrew W Jacobs

Eric J Horvitz

Carl Myers Kadie

David O Hovel

Joseph K Ollis

Gregory P Baribault

Marc A Smith

Galen Clyde Hunt

James William Scott

Oscar E Murillo

Raman Kumar Sarin

Alice Jane Bernheim Brush

Danyel Aharon Fisher

Barry Clayton Bond

Eric I Horvitz

Amy Kathleen Karlson

Dominique Fortier

Scott Joseph Counts

Alice Jane Brush

Carman G Neustaedter

Techniques for creating breadcrumbs for a trail of activity are described. The trail of activity may be created by recording movement information based on inferred actions of walking, not walking, or changing floor levels. The movement information may be recorded with an accelerometer and a pressure sensor. A representation of a list of breadcrumbs may be visually displayed on a user interface of a mobile device, in a reverse order to retrace steps. In some implementations, a compass may additionally or alternatively be used to collect directional information relative to the earth's magnetic poles.

Retracing steps

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

A unique system, method, and user interface that facilitate ordering personal items based on past personal interaction between a user and the user's correspondents are provided. In particular, the system provides alternative views of information, such as messages, that is organized around people using an ordering based on the history of communication between the recipient and sender. Social metrics can be calculated based on social metadata associated with the messages, for example. Metrics can be used to configure how or which messages are viewed and their order in one or more pane views. Each pane view can present different orderings of messages&#x2014;which are displayed by the recipient or sender of the message. So for instance, instead of viewing messages in chronological receipt date, they can be viewed by the message's sender and ordered by the number of messages previously sent to the user.

Ordering personal information using social metadata

Systems and methods that infer and classify user activity based in part on routing data. A storage medium can store raw data collected, and such acquired data can be subsequently be analyzed or distilled to generate abstract qualities about the raw data (e.g., velocity of user during route, level of difficulty, and the like). Various machine learning techniques, artificial intelligence methodologies, decision trees, and/or statistical methods can be employed to supply inference regarding the acquired raw data and/or the abstract qualities.

Activity classification from route and sensor-based metadata

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.

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

A system and methods 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.

A system and method for personalizing an information classifier is provided. The system includes a default or universal classifier that is pre-trained with features that have relatively universal discriminatory relationships for multiple people and that is operable to produce a measure that a message is classified as having one of several characteristics. The system further includes a second classifier that is constructed and personalized through training via a more general search through the space of potentially discriminatory features. The second classifier, after personalization, is intended to classify information at a level exceeding that of the first classifier based on the specific preferences, habits, and desires of the user who personalizes the second classifier. The system further includes a weighting component that facilitates a combining component producing an integrated measure based on input from both the first classifier and the second classifier.

System and method for constructing and personalizing a universal information classifier

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 ().

A source wireless device is capable of transmitting items over a wireless network using a number of different wireless transfer mechanism such as, for example, Infra-Red (IR) or Bluetooth. Several potential destination wireless devices may be capable of receiving the item using at least one of the different wireless transfer mechanisms. The user selects one or more destination wireless devices to send items to using a unified user interface that lists the various potential destination wireless devices. After a user selects items to transfer as well as the destination wireless device(s), the wireless transfer mechanism appropriate for transfer to each device is then automatically identified without requiring user selection of the particular wireless transfer mechanism.

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Seattle, WA, United States of America

Andrew W Jacobs