Abstract: A statistical methodology is employed for assisting people with the setting of parameters of software applications or services. With the method, information about demographics and/or about the complete or partial preferences of other people, are analyzed to infer recommendations for settings and functionality of a computer application or service. A system is reviewed with the ability to receive data regarding a plurality of users, and stores respective profiles for these users in a community store. The system can leverage off of these completed and/or partially completed profiles of parameters representing preferences about software operation in connection with building new profiles for users (new and/or existing). Data regarding a user that desires to build a new profile is employed in connection with the community profiles to facilitate the user building a personalized profile.

Abstract: An information delivery system comprises a receiver component that receives information about the movement, velocity, acceleration, and/or locations over time of a user. A computation component using a predictive model generates a probability distribution relating to one or more of when the user will next be stopped, how long the user will be stopped, how long a pattern of motion, such as walking, driving in stop and go traffic, and smooth highway motion will last, based at least in part upon signals about motion over time. The system can further comprise an alerting component that determines when to provide the user with information based at least in part upon the probability distribution over some aspect of motion or cessation of motion, and optionally the content, or tagged or inferred urgency or importance, of a message or communication.

Abstract: An information delivery system comprises a receiver component that receives information about the movement, velocity, acceleration, and/or locations over time of a user. A computation component using a predictive model generates a probability distribution relating to one or more of when the user will next be stopped, how long the user will be stopped, how long a pattern of motion, such as walking, driving in stop and go traffic, and smooth highway motion will last, based at least in part upon signals about motion over time. The system can further comprise an alerting component that determines when to provide the user with information based at least in part upon the probability distribution over some aspect of motion or cessation of motion, and optionally the content, or tagged or inferred urgency or importance, of a message or communication.

Abstract: A task disruption and recovery system and methods are described that detects shifts away from ongoing tasks, whether by self-interruption or by disruptive events from within or outside a computing system, based on signals detected. Among other functions, the system works to enhance the efficient recovery of suspended tasks or problem-solving sessions via storing and presenting representations of the suspended sessions in a manner that facilitates recovery and continuation.

Abstract: An information delivery system comprises a receiver component that receives information about the movement, velocity, acceleration, and/or locations over time of a user. A computation component using a predictive model generates a probability distribution relating to one or more of when the user will next be stopped, how long the user will be stopped, how long a pattern of motion, such as walking, driving in stop and go traffic, and smooth highway motion will last, based at least in part upon signals about motion over time. The system can further comprise an alerting component that determines when to provide the user with information based at least in part upon the probability distribution over some aspect of motion or cessation of motion, and optionally the content, or tagged or inferred urgency or importance, of a message or communication.

Abstract: The claimed subject matter provides systems and/or methods that facilitate generating an inference about events that may not have yet been observed. Open-world modeling can be used to take a history of observation so as to understand trends over time in the revelation of previously unseen events, and to make inferences with subsets of data that new unseen events will be seen. Thus, inaccuracies associated with predictions generated from incomplete data sets can be mitigated. To yield such predictions, open-world submodels and closed-world submodels that do not allow for previously unseen events can be combined via a model mixture methodology, which fuses inferences from the open- and close-world models.

Abstract: The claimed subject matter provides systems and/or methods that facilitate generating an inference about events that may not have yet been observed. Open-world modeling can be used to take a history of observation so as to understand trends over time in the revelation of previously unseen events, and to make inferences with subsets of data that new unseen events will be seen. Thus, inaccuracies associated with predictions generated from incomplete data sets can be mitigated. To yield such predictions, open-world submodels and closed-world submodels that do not allow for previously unseen events can be combined via a model mixture methodology, which fuses inferences from the open- and close-world models.

Abstract: The claimed subject matter provides systems and/or methods that facilitate generating an inference about events that may not have yet been observed. Open-world modeling can be used to take a history of observation so as to understand trends over time in the revelation of previously unseen events, and to make inferences with subsets of data that new unseen events will be seen. Thus, inaccuracies associated with predictions generated from incomplete data sets can be mitigated. To yield such predictions, open-world submodels and closed-world submodels that do not allow for previously unseen events can be combined via a model mixture methodology, which fuses inferences from the open- and close-world models.

Abstract: A sensing and context management architecture that can detect that a user is interacting with a given device and in an associated context, and in response thereto, manages device processes as the user moves from device to device, location to location, and/or context to context. The invention comprises a system that facilitates management of a user situation or context. A sensing component is provided that senses a context of a user by way of one or more sensors and/or a particular device with which the user is interacting in the context, for example, and a management component that manages the device and/or one or more services in the context according to rules or inferences user preferences, sensed observations, and user input data.

Abstract: A statistical methodology is employed for assisting people with the setting of parameters of software applications or services. With the method, information about demographics and/or about the complete or partial preferences of other people, are analyzed to infer recommendations for settings and functionality of a computer application or service. A system is reviewed with the ability to receive data regarding a plurality of users, and stores respective profiles for these users in a community store. The system can leverage off of these completed and/or partially completed profiles of parameters representing preferences about software operation in connection with building new profiles for users (new and/or existing). Data regarding a user that desires to build a new profile is employed in connection with the community profiles to facilitate the user building a personalized profile.

Abstract: A statistical methodology is employed for assisting people with the setting of parameters of software applications or services. With the method, information about demographics and/or about the complete or partial preferences of other people, are analyzed to infer recommendations for settings and functionality of a computer application or service. A system is reviewed with the ability to receive data regarding a plurality of users, and stores respective profiles for these users in a community store. The system can leverage off of these completed and/or partially completed profiles of parameters representing preferences about software operation in connection with building new profiles for users (new and/or existing). Data regarding a user that desires to build a new profile is employed in connection with the community profiles to facilitate the user building a personalized profile.

Abstract: Sensing, learning, inference, and route analysis methods are described that center on the development and use of models that predict road speeds. In use, the system includes a receiver component that receives a traffic system representation, the traffic system representation includes velocities for a plurality of road segments over different contexts. A predictive component analyzes the traffic system representation and automatically assigns velocities to road segments within the traffic system representation, thereby providing more realistic velocities for different contexts where only statistics and/or posted speed limits were available before.

Abstract: An information delivery system comprises a receiver component that receives information about the movement, velocity, acceleration, and/or locations over time of a user. A computation component using a predictive model generates a probability distribution relating to one or more of when the user will next be stopped, how long the user will be stopped, how long a pattern of motion, such as walking, driving in stop and go traffic, and smooth highway motion will last, based at least in part upon signals about motion over time. The system can further comprise an alerting component that determines when to provide the user with information based at least in part upon the probability distribution over some aspect of motion or cessation of motion, and optionally the content, or tagged or inferred urgency or importance, of a message or communication.

Abstract: An information delivery system comprises a receiver component that receives information about the movement, velocity, acceleration, and/or locations over time of a user. A computation component using a predictive model generates a probability distribution relating to one or more of when the user will next be stopped, how long the user will be stopped, how long a pattern of motion, such as walking, driving in stop and go traffic, and smooth highway motion will last, based at least in part upon signals about motion over time. The system can further comprise an alerting component that determines when to provide the user with information based at least in part upon the probability distribution over some aspect of motion or cessation of motion, and optionally the content, or tagged or inferred urgency or importance, of a message or communication.

Abstract: A task disruption and recovery system and methods are described that detects shifts away from ongoing tasks, whether by self-interruption or by disruptive events from within or outside a computing system, based on signals detected. Among other functions, the system works to enhance the efficient recovery of suspended tasks or problem-solving sessions via storing and presenting representations of the suspended sessions in a manner that facilitates recovery and continuation.

Abstract: The claimed subject matter provides systems and/or methods that facilitate generating an inference about events that may not have yet been observed. Open-world modeling can be used to take a history of observation so as to understand trends over time in the revelation of previously unseen events, and to make inferences with subsets of data that new unseen events will be seen. Thus, inaccuracies associated with predictions generated from incomplete data sets can be mitigated. To yield such predictions, open-world submodels and closed-world submodels that do not allow for previously unseen events can be combined via a model mixture methodology, which fuses inferences from the open- and close-world models.

Abstract: An information delivery system comprises a receiver component that receives information about the movement, velocity, acceleration, and/or locations over time of a user. A computation component using a predictive model generates a probability distribution relating to one or more of when the user will next be stopped, how long the user will be stopped, how long a pattern of motion, such as walking, driving in stop and go traffic, and smooth highway motion will last, based at least in part upon signals about motion over time. The system can further comprise an alerting component that determines when to provide the user with information based at least in part upon the probability distribution over some aspect of motion or cessation of motion, and optionally the content, or tagged or inferred urgency or importance, of a message or communication.

Abstract: Sensing, learning, inference, and route analysis methods are described that center on the development and use of models that predict road speeds. In use, the system includes a receiver component that receives a traffic system representation, the traffic system representation includes velocities for a plurality of road segments over different contexts. A predictive component analyzes the traffic system representation and automatically assigns velocities to road segments within the traffic system representation, thereby providing more realistic velocities for different contexts where only statistics and/or posted speed limits were available before.

Abstract: Methods and architectures for context-sensitive reminding and service facilitating are disclosed. The architectures monitor user context and activity, senses or infers relevant reminders, goals, such as those that come from a growing need of the user that should be fulfilled, and computes best reminders, and recommend plans on fulfilling need(s) in an optimum way. Statistical models of a user's knowledge and recall in different settings may be employed. Facilities, services, and merchants can be identified along a route that the user can take, and cost-benefit analysis is performed for determining which merchant(s) to select to fulfill the need(s). Routes may be created as opportunistic modifications of trips underway. Merchants can respond back with offers of sale to the user for all available needed items, and the user can respond with acceptance or denial of the offers. Merchants can also respond in a bidding fashion in order to gain user's patronage.