Abstract:
Methods, systems, apparatus, including computer programs encoded on computer storage medium, to facilitate identification of additional trigger-terms for a structured information card. In one aspect, the method includes actions of accessing data associated with a template for presenting structured information, wherein the accessed data references (i) a label term and (ii) a value. Other actions may include obtaining a candidate label term, identifying one or more entities that are associated with the label term, identifying one or more of the entities that are associated with the candidate label term, and for each particular entity of the one or more entities that are associated with the candidate label term, associating, with the candidate label term, (i) a label term that is associated with the particular entity, and (ii) the value associated with the label term.
Abstract:
A computing device may receive a communication sent from an external computing device. At least one processor of the computing device may determine, using an on-device machine-trained model and based at least in part on the communication, one or more candidate responses to the communication. The at least one processor may receive an indication of a user input that selects a candidate response from the one or more candidate responses. Responsive to receiving the indication of the user input that selects the candidate response, the at least one processor may send the candidate response to the external computing device.
Abstract:
A method includes identifying images associated with a user, where the image is identified as at least one of captured by a user device associated with the user, stored on the user device associated with the user, and stored in cloud storage associated with the user. The method also includes for each of the images, determining one or more labels, wherein the one or more labels are based on at least one of metadata and a primary annotation. The method also includes generating a mapping of the one or more labels to one or more confidence scores, wherein the one or more confidence scores indicate an extent to which the one or more labels apply to corresponding images. The method also includes interacting with the user to obtain identifying information that is used to categorize one or more of the images.
Abstract:
Methods and apparatus related to identifying a category for a task that is associated with a user and populating annotation fields related to the task based on the category of the task. The task and populated annotation fields may be provided for use by one or more application to provide a task completion step to the user. In some implementations, the category may be identified based on input from the user, documents of the user, and/or data that are associated with the user. In some implementations, a completion step for the task may be suggested to the user by an application that accesses the task and populated annotated information. In some implementations, multiple applications may suggest different completion steps to the user for the same task.
Abstract:
Methods and apparatus related to providing one or more completion step suggestions for a task that is associated with a user. In some implementations, the completion step suggestions may be provided to the user based on the satisfaction of a trigger condition. In some implementations, a trigger condition may be based on a user geographic location. In some implementations, a trigger condition may be based on an action of the user. In some implementations, a trigger condition may be based on a time when the associated task may be completed.
Abstract:
Methods and apparatus related to providing one or more completion step suggestions for a task that is associated with a user. In some implementations, the completion step suggestions may be provided to the user based on the satisfaction of a trigger condition. In some implementations, a trigger condition may be based on a user geographic location. In some implementations, a trigger condition may be based on an action of the user. In some implementations, a trigger condition may be based on a time when the associated task may be completed.
Abstract:
Methods, systems, apparatus, including computer programs encoded on computer storage medium, to facilitate identification of additional trigger-terms for a structured information card. In one aspect, the method includes actions of accessing data associated with a template for presenting structured information, wherein the accessed data references (i) a label term and (ii) a value. Other actions may include obtaining a candidate label term, identifying one or more entities that are associated with the label term, identifying one or more of the entities that are associated with the candidate label term, and for each particular entity of the one or more entities that are associated with the candidate label term, associating, with the candidate label term, (i) a label term that is associated with the particular entity, and (ii) the value associated with the label term.
Abstract:
Methods and apparatus related to providing one or more completion step suggestions for a task that is associated with a user. In some implementations, the completion step suggestions may be provided to the user based on the satisfaction of a trigger condition. In some implementations, a trigger condition may be based on a user geographic location. In some implementations, a trigger condition may be based on an action of the user. In some implementations, a trigger condition may be based on a time when the associated task may be completed.
Abstract:
Systems and methods for adding labels to a graph are disclosed. One system includes a plurality of computing devices including processors and memory storing an input graph generated based on a source data set, where an edge represents a similarity measure between two nodes in the input graph, the input graph being distributed across the plurality of computing devices, and some of the nodes are seed nodes associated with one or more training labels from a set of labels, each training label having an associated original weight. The memory may also store instructions that, when executed by the processors, cause the plurality of distributed computing devices to propagate the training labels through the input graph using a sparsity approximation for label propagation, resulting in learned weights for respective node and label pairs, and automatically update the source data set using node and label pairs selected based on the learned weights.
Abstract:
Methods, apparatus, systems, and computer-readable media are provided for classifying, or “labeling,” documents such as emails en masse based on association with a cluster/template. In various implementations, a corpus of documents may be grouped into a plurality of disjoint clusters of documents based on one or more shared content attributes. A classification distribution associated with a first cluster of the plurality of clusters may be determined based on classifications assigned to individual documents of the first cluster. A classification distribution associated with a second cluster of the plurality of clusters may then be determined based at least in part on the classification distribution associated with the first cluster and a relationship between the first and second clusters.