The Aro Corporation

Microsoft Technology Licensing, LLC

Jonathan D Lazarus

Kevin Francis Eustice

Michael Perkowitz

Kenji Kawai

Patrick James Ferrel

Lester L Waters

Meliha Yetisgen-Yildiz

Nolan Lawson

Steven M Reed

Ned Dykstra Hayes

Kenneth Dwight Krossa

A user interface for an electronic calendar represents different locations or different users or different user calendars in different portions of the display. Calendar entries can be associated with one or more locations, one or more users, and with one or more user calendars. The different locations may reside in different time zones and a timeline for each time zone is displayed. The position of the calendar entry provides a visual identifier of the timeline with which the event is associated. Travel time to and from events in the calendar are calculated for calendared events and shown adjacent to the beginning and end of the event. A user's future location at a point in time is inferred from patterns in the user's locations and by analyzing the user's calendared events and correspondence in order to calculate travel time to calendared events.

Calendaring location-based events and associated travel

A social network model, based on data relevant to a user, is used for semantic processing to enable improved entity recognition among text accessed by the user. An entity extraction module of the server, with reference to a general training corpus, general gazetteers, user-specific gazetteers, and entity models, parses text to identify entities. The entities may be, for example, people, organizations, or locations. A social network module of the server builds the social network model implicit in the data accessed by the user. The social network model includes the relationships between entities and an indication of the strength of each relationship. The social network module is also used to disambiguate names and unify entities based on the social network model.

Social network model for semantic processing

An entity recognition model is trained to use gazetteers to recognize entities referenced in documents. When a document associated with a user is received for recognizing entities referenced therein, a gazetteer is selected based on user contexts associated with the user. The document is analyzed using the gazetteer according to the entity recognition model to recognize an entity referenced therein. Additional facts associated with the recognized entities and actions applicable to the recognized entities are provided to enable the user to perform the applicable actions against the recognized entity.

Dynamic gazetteers for entity recognition and fact association

Several approaches to serializing a disc may be used in the present invention. First, portions of a disc (such as sector(s) or track(s)) may be physically damaged to create a pattern of damage that somewhat uniquely identifies the disc. A number of different techniques may be used to damage the disc. For instance, laser devices may be used, sharp devices may be used or a master disc may be configured to create the damage. The physical damage may be used in conjunction with soft damage that is encoded in software on the disc. Alternatively, certain soft damage approaches may be used separately to serialize the disc.

Disc serialization

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Mercer Island, WA, United States of America

Jonathan D Lazarus