Abstract: The present invention provides methods for using abstractions of people, including dynamic and static groups of people, to enhance the efficiency of the specification and automation of policies for sharing information between users with a “need-to-know.” An instance of the present invention can also provide these users information based on a “time-to-know.” By providing access to information based on group affiliation and properties of the content of the information, the present invention maintains optimal information privacy while minimizing encumbrances to sharing data with appropriate users and even at appropriate times. The present invention can be integrated with other communication technologies to facilitate access to information in a time appropriate manner. Other instances of the present invention employ automated and semi-automated, mixed-initiative techniques, to make information-sharing decisions.

Abstract: The discussion relates to route safety. One example can obtain crash probabilities for road routes for driving between two points. The example can present multiple individual road routes that reflect both crash probabilities and estimated times between the two points. The example can receive an indication that a user selected an individual one of the multiple individual road routes. The example can provide driving instructions for the selected individual one of the multiple individual road routes.

Abstract: The subject disclosure is directed towards resolving an uncertain transportation context by suggesting one or more potential diversions. An automated routing system may generate routing information that includes map data as well as a location of a diversion having an expected cost in compliance with the uncertain transportation context. Such a diversion may be a waypoint that satisfies one or more user needs given an unknown/uncertain destination.

Abstract: The subject disclosure is directed towards processing evidence, which may include high-dimensional streaming evidence, into a future belief state. The existing evidence is used to project a belief about a future state. The future belief state may be used to determine whether to wait for additional evidence, or to act now without waiting for additional evidence, e.g., based on a cost of the delay. For example, an autonomous assistant may decide based upon the belief whether to engage a person or not, or to wait for more information before the engagement decision is made.

Abstract: The present invention provides methods for using abstractions of people, including dynamic and static groups of people, to enhance the efficiency of the specification and automation of policies for sharing information between users with a “need-to-know.” An instance of the present invention can also provide these users information based on a “time-to-know.” By providing access to information based on group affiliation and properties of the content of the information, the present invention maintains optimal information privacy while minimizing encumbrances to sharing data with appropriate users and even at appropriate times. The present invention can be integrated with other communication technologies to facilitate access to information in a time appropriate manner. Other instances of the present invention employ automated and semi-automated, mixed-initiative techniques, to make information-sharing decisions.

Abstract: Described are methods that utilize a geographic location technology (e.g., GPS) to determine user location data, and existing network-based websites (e.g., Internet websites) for searching and accessing data related to the location data such that the user context can be developed and stored. A location component is provided that determines location data of a wireless communications device of a user. A context component is provided that accesses context data based on the location data to define a context in which the device is located. Activities, goals, and overall context of a user can be inferred through statistical fusion of multiple sources of evidence. The context data is presented to the user via the wireless device such that the user can make decisions as to where to go, for example. User preferences can be accessed and applied to filter context data according to what the user desires to see and access.

Abstract: The subject disclosure is directed towards the use of Monte Carlo (MC) procedures for computing the value of information (VOI), including with long evidential sequences. An MC-VOI algorithm is used to output a decision as to balancing the value and costs of collecting information in advance of taking action by running prediction model-based simulations to determine execution paths through possible states, and processing the results of the simulations/paths taken into a final decision.

Abstract: The subject disclosure is directed towards processing evidence, which may include high-dimensional streaming evidence, into a future belief state. The existing evidence is used to project a belief about a future state. The future belief state may be used to determine whether to wait for additional evidence, or to act now without waiting for additional evidence, e.g., based on a cost of the delay. For example, an autonomous assistant may decide based upon the belief whether to engage a person or not, or to wait for more information before the engagement decision is made.

Abstract: The present invention provides methods for using abstractions of people, including dynamic and static groups of people, to enhance the efficiency of the specification and automation of policies for sharing information between users with a “need-to-know.” An instance of the present invention can also provide these users information based on a “time-to-know.” By providing access to information based on group affiliation and properties of the content of the information, the present invention maintains optimal information privacy while minimizing encumbrances to sharing data with appropriate users and even at appropriate times. The present invention can be integrated with other communication technologies to facilitate access to information in a time appropriate manner. Other instances of the present invention employ automated and semi-automated, mixed-initiative techniques, to make information-sharing decisions.

Abstract: The subject disclosure pertains to web searches and more particularly toward influencing resultant content to increase relevancy. The resultant content can be influenced by reconfiguring a query and/or filtering results based on user location and/or context information (e.g., user characteristics/profile, prior interaction/usage temporal, current events, and third party state/context . . . ). Furthermore, the disclosure provides for query execution on at least a subset of designated web content, for example as specified by a user. Still further yet, a localized marketing system is disclosed that provides discount offers to users that match merchant criteria including proximity. A system for actively probing populations of users with different parameters and monitoring responses can be employed to collect data for identifying the best discounts and deadlines to offer to users to achieve desired results.

Abstract: The subject disclosure pertains to web searches and more particularly toward influencing resultant content to increase relevancy. The resultant content can be influenced by reconfiguring a query and/or filtering results based on user location and/or context information (e.g., user characteristics/profile, prior interaction/usage temporal, current events, and third party state/context . . . ). Furthermore, the disclosure provides for query execution on at least a subset of designated web content, for example as specified by a user. Still further yet, a localized marketing system is disclosed that provides discount offers to users that match merchant criteria including proximity. A system for actively probing populations of users with different parameters and monitoring responses can be employed to collect data for identifying the best discounts and deadlines to offer to users to achieve desired results.

Abstract: The subject disclosure is directed towards the use of Monte Carlo (MC) procedures for computing the value of information (VOI), including with long evidential sequences. An MC-VOI algorithm is used to output a decision as to balancing the value and costs of collecting information in advance of taking action by running prediction model-based simulations to determine execution paths through possible states, and processing the results of the simulations/paths taken into a final decision.

Abstract: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.

Abstract: Systems, methods, and devices are described for implementing map matching techniques relating to measured location data. Probabilistic models, including temporal Bayesian network models and Hidden Markov Models, may be used for combining multiple classes of evidence relating to potential locations of points traversed on routes over time. Multiple route segments and overall routes may be maintained under relative uncertainty as candidates. The candidate route segments and overall routes may then be reduced into a smaller number of candidates or a single most likely route as a trip progresses. As the trip progresses, route segments in proximity to each location point are identified and candidate matches are determined. A probability of an entity traversing a candidate match at a given time and a probability of an entity traversing between a first candidate match at a first time and a second candidate match at a second time are determined based on a plurality of factors.

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: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.

Abstract: Architecture that monitors interaction data (e.g., search queries, query results and click-through rates), and provides users with links to other users that fall into similar categories with respect to the foregoing monitored activities (e.g., providing links to individuals and groups that share common interests and/or profiles). A search engine can be interactively coupled with one or more social networks, and that maps individuals and/or groups within respective social networks to subsets of categories associated with searches. A database stores mapped information which can be continuously updated and reorganized as links within the system mapping become stronger or weaker. The architecture can comprise a social network system that includes a database for mapping search-related information to an entity of a social network, and a search component for processing a search query for search results and returning a link to an entity of a social network based on the search query.

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 system for predicting variability of travel time for a trip at a particular time may utilize a machine learning model including latent variables that are associated with the trip. The machine learning model may be trained from historical trip data that is based on location-based measurements reported from mobile devices. Once trained, the machine learning model may be utilized for predicting variability of travel time. A process may include receiving an origin, a destination, and a start time associated with a trip, obtaining candidate routes that run from the origin to the destination, and predicting, based at least in part on the machine learning model, a probability distribution of travel time for individual ones of the candidate routes. One or more routes may be recommended based on the predicted probability distribution, and a measure of travel time for the recommended route(s) may be provided.

Abstract: The subject disclosure is directed towards the use of Monte Carlo (MC) procedures for computing the value of information (VOI), including with long evidential sequences. An MC-VOI algorithm is used to output a decision as to balancing the value and costs of collecting information in advance of taking action by running prediction model-based simulations to determine execution paths through possible states, and processing the results of the simulations/paths taken into a final decision.