Abstract: Systems, methods, and computer-readable storage media are provided for sharing user-information with bots. An automated task to be performed on behalf of a user is determined from at least one user message provided to a user interface of a first bot. A second bot is determined that is capable of performing the automated task on behalf of the user. User information of the user to provide to the second bot for the performing of the automated task is determined. Content of the user information is based on a trust level of the second bot and service parameters for completing the automated task. The first bot provides the determined user information to the second bot using one or more network communications.

Abstract: Incoming mail messages for a user may be ranked, modified, and/or summarized based on a number of factors, including characteristics of the user computing devices used for accessing email and the user's current context. User context may include location, whether the user is currently driving, how much time the user has to read email messages, etc. Features of incoming email messages are analyzed, including length, attachments, sender, etc. User-related activity and characteristics of the user's computing devices are determined and analyzed to determine a user context, for instance, the user's location, mode of movement, time slot available for the user to read email messages, upcoming events on the user's calendar, etc. The email messages are then ranked according to the user context and/or user computing device characteristics. At least a portion of the email messages are provided for presentation via a user computing device based on the ranking.

Abstract: One or more techniques and/or systems are provided for constructing a complementary calendar and/or a shadow calendar. A user may maintain a primary calendar within which the user may schedule user specified tasks and/or meetings, but may inadvertently omit other entries. Accordingly, a complementary calendar may be constructed based upon inferences derived from user signal data (e.g., information used to identify/infer activities of the user, such as social network profile information, messages, temporal information, locational information, documents, etc.). The complementary calendar may be automatically populated with entries corresponding to inferences derived from user signals and/or real-time conditions (e.g., weather, store hours, traffic conditions, etc.). The primary calendar and the complementary calendar may be merged to create a shadow calendar.

Abstract: A method for inferring venue visits using semantic information includes receiving sensor data from sensors. An indication of a location is received that is associated with a user and determined based on the sensor data. A set of candidate venues associated with the location is determined based on the indication of the location. Sets of semantic information associated with the set of candidate venues are determined based on the sensor data. Candidate venues of the set are ranked by confidence that a given candidate venue corresponds to a visited venue of a venue visit based on the set of semantic information associated with the given candidate venue and additional semantic information associated with the user. A highest ranked candidate venue is selected as the visited venue and an indication is provided to a service causing content to be presented to the user based on the selected visited venue.

Abstract: Methods for providing enhanced services to users participating in communication sessions (CS), via a virtual assistant, are disclosed. One method receives content that is exchanged by users participating in the CS. The content includes natural language expressions that encode a conversation carried out by users. The method determines content features based on natural language models. The content features indicate intended semantics of the natural language expressions. The method determines a relevance of the content and identifies portions of the content that are likely relevant to the user. Determining the relevance is based on the content features, a context of the CS, a user-interest model, and a content-relevance model of the natural language models. Identifying the likely relevant content is based on the determined relevance of the content and a relevance threshold. A summary of the CS is automatically generated from summarized versions of the likely relevant portions of the content.

Abstract: Intelligent agents (IA) for automatically generating responses to content within a communication session (CS) are disclosed. An IA is trained to target the responses to a user and the user's context within the CS. An IA receives CS content that includes natural language expressions encoding users' conversations and determines content features based on natural language models. The content features indicate intended semantics of the expressions. The IA identifies likely-relevant content to the targeted user, to generate a response for. Identifying such content includes determining a relevance of the content based on content features, a context of the CS, a user-interest model, and a content-relevance model. Identifying the likely-relevant content to respond to is based on the determined relevance of the content and relevance thresholds. Various responses to the identified portions of the content are automatically generated and provided based on a natural language response-generation model targeted to the user.

Abstract: The presently disclosed subject matter includes a camera system for aerial photography applications which can be mounted on an aircraft and be operated for obtaining images of a surveyed area. The proposed camera system comprises a camera control unit operatively connected to a camera supported by a pivotal supporting device such as a gimbal assembly. The camera is continuously moved along a scanning line without stopping and is operated to capture images in a certain frame rate, this is carried out by measuring as well as regulating the angular velocity of the camera to adapt the pictured and the non-pictures zones over the scanning line.

Abstract: One or more techniques and/or systems are provided for constructing a complementary calendar and/or a shadow calendar. A user may maintain a primary calendar within which the user may schedule user specified tasks and/or meetings, but may inadvertently omit other entries. Accordingly, a complementary calendar may be constructed based upon inferences derived from user signal data (e.g., information used to identify/infer activities of the user, such as social network profile information, messages, temporal information, locational information, documents, etc.). The complementary calendar may be automatically populated with entries corresponding to inferences derived from user signals and/or real-time conditions (e.g., weather, store hours, traffic conditions, etc.). The primary calendar and the complementary calendar may be merged to create a shadow calendar.

Abstract: Personalized reminder notifications are provided regarding communication-related events. The reminders correspond to missed communications or events unaddressed by a user, and may be determined based on sensor data provided by a user device. Further, an urgency level for the unaddressed event and a user availability model for responding to the event may be determined. The model may include a set of scores corresponding to the user's capability for carrying out tasks associated with responding to the unaddressed event, such as composing email or initiating a call. Additionally, reminder notification content may be generated based on information about availability and the unaddressed event, and used to provide notification(s). The notification content may include a recommendation to present a notification to the user at a future time determined likely to be convenient for the user to respond to the event or where the user likely will have capacity to respond appropriately.

Abstract: Personalized notifications are provided to a user. The notifications correspond to events, which can include information items, unaddressed or unnoticed by a user. The unaddressed events may be determined based on sensor data provided by a user device associated with the user including user activity pattern information. Further, an urgency level of the unaddressed event and user availability for responding to the event may be determined. The availably may comprise a model with score(s) corresponding to the user's capability for carrying out tasks associated with addressing the event. Additionally, notification content may be generated based on information about availability and the unaddressed event, and used to provide notification(s). The notification content may include a recommendation to present a notification to the user at a time determined likely to be convenient for the user to be notified of the event or where the user likely has capacity to address the event appropriately.

Abstract: Disclosed in some examples are methods, systems, machine-readable media, and devices to provide a personalized experience, by making user data available to a skill in a personal assistant service. In an example, a third-party skill such as an automated bot may obtain user data (such as user profile and contextual information at runtime) to personalize and adjust an interaction to the user. Operations to implement the techniques may include: providing a data interface of the personal assistant service to expose user data maintained by the personal assistant service, based on user data privacy settings and third-party skill permissions; receiving a request from the third-party skill, via the data interface, to obtain the user data to in connection with performing some action of the third-party skill; and providing the user data to the third-party skill in response to the request, based on the permission settings and the privacy settings.

Abstract: In some implementations, a user schedule is constructed comprising planned events of a user. It is determined that a planned event of the planned events corresponds to a divergence from a pattern of detected instances of a routine of the user based on user activity data from a set of sensors. An occurrence of an event of the user is determined from the user activity data. It is determined the divergence failed to occur based on the occurrence of the event and the user schedule. Based on the determining the divergence failed to occur, content associated with the routine is caused to be presented on a user device.

Abstract: One or more techniques and/or systems are provided for constructing a complementary calendar and/or a shadow calendar. A user may maintain a primary calendar within which the user may schedule user specified tasks and/or meetings, but may inadvertently omit other entries. Accordingly, a complementary calendar may be constructed based upon inferences derived from user signal data (e.g., information used to identify/infer activities of the user, such as social network profile information, messages, temporal information, locational information, documents, etc.). The complementary calendar may be automatically populated with entries corresponding to inferences derived from user signals and/or real-time conditions (e.g., weather, store hours, traffic conditions, etc.). The primary calendar and the complementary calendar may be merged to create a shadow calendar.

Abstract: Systems, methods, and computer-readable storage media are provided for automating personalized out-of-the-box and ongoing in-application settings. A triggering event is detected for an exchange of information between an information service and one or more application or service. A trust level and domain of information of the one or more application or service is determined. Based on the trust level and domain of information, information to be shared with the one or more application or service is identified and the identified information is shared. The information to be shared can be all of the requested information, some of the requested information, or none of the requested information.

Abstract: Technology is disclosed for providing user control over content presented on personal computing devices (i.e., user devices). A current context associated with a user device is determined, and a set of personalized metadata characterizing content items is received. Based on the current context associated with the user device, and the set of personalized metadata, instructions may be generated to modify the presentation of any content, such as by concealing or revealing certain content items.

Abstract: Technology is disclosed for improving user privacy and providing user control over user-activity data collected from personal computing devices (i.e., user devices). User devices may be configured to operate in a private mode that enables a user to control, for example, which aspects of user-activity data are provided to applications and services running on their user device; to obscure or modify aspects of user-activity data so that certain applications and services, which may require this information to operate, may still function, but that the obscured information provided to these applications and services preserves user privacy or no longer may be used to identify the user; or to remove evidence of user-activity data created, monitored, reported, or otherwise collected by or on the user device while the user is operating their user device in the private mode setting.

Abstract: Systems and methods are provided for associating meetings with projects. Some implementations include evaluating a similarity between a conversation between two or more users and a set of keywords characterizing at least one project associated with a user of the two or more users, where the conversation is captured by sensor data. Based on the similarity, a listening mode is activated on a user device associated with the user. Contextual information associated with the conversation is generated from portions of the sensor data provided by the activated listening mode. A meeting corresponding to the conversation is assigned to a project associated with the user based on the contextual information. Content is personalized to the user based on the assignment of the meeting to the project.

Abstract: Systems, methods, and computer-readable storage media are provided for enabling discovery of a user by a member of an inner circle of the member when the user is in close proximity to the member. An indication is received from a user device indicating members of an inner circle of the user. A private key is sent to the mobile devices of each member of the inner circle. When the user device broadcasts an encrypted identifier, member devices with the private key can decrypt the encrypted identifier, allowing the member to discover that the user is in close proximity The user can also update membership of the inner circle so that only members presently in the inner circle can discover that the user is in close proximity.

Abstract: Systems and methods are provided for associating project entities with projects. In various implementations, user activity data is monitored based on sensor data from at least one user device associated with a user. From the monitored user activity data, entity features are determined of project entities corresponding to the user activity data. Time slots are extracted from the project entities. The time slots are clustered based the entity features of ones of the project entities corresponding to the time slots. The project entities are grouped into projects based on the clustered time slots. Project tags corresponding to the projects are applied to the project entities based on the grouping of the project entities. Content is personalized to the user based on the project tags applied to the project entities.

Abstract: In some implementations, a method includes extracting completion criteria of an action item and parameters of the completion criteria from a message portion of a user message between users. In response to determining, from sensor data provided by one or more sensors associated with a user, the user practices a routine, a routine-related aspect is generated from a user routine model of the user for the routine. It is inferred that at least one of the extracted completion criteria of the action item is unsatisfied based on the extracted parameters and the identified routine-related aspect. Based on the inferring, a notification is provided to at least one user associated with the action item.