Abstract: Methods, systems, and apparatus for receiving a query image and a user tap location, processing the received query image based on the user tap location, identifying one or more entities associated with the processed query image and in response to receiving (i) the query image, and (ii) the user tap location, providing information about the identified one or more of the entities.

Abstract: Methods, systems, and apparatus for receiving a query image, receiving one or more entities that are associated with the query image, identifying, for one or more of the entities, one or more candidate search queries that are pre-associated with the one or more entities, generating a respective relevance score for each of the candidate search queries, selecting, as a representative search query for the query image, a particular candidate search query based at least on the generated respective relevance scores and providing the representative search query for output in response to receiving the query image.

Abstract: Systems and methods are provided for sharing a screen from a mobile device. For example, a method includes receiving, at a second mobile device, an image of a screen captured from a first mobile device and determining whether to trigger an automated action. The method may also include displaying, responsive to not triggering the automated action, annotation data generated for the image with the image on a display of the second mobile device, the annotation data including at least one visual cue corresponding to content in the image relevant to a user of the second mobile device. The method may further include, responsive to triggering the automated action, determining that a mobile application associated with the image is installed on the second mobile device and replaying user input actions received with the image on the second mobile device starting from a reference screen associated with the mobile application.

Abstract: Embodiments retrieve a set of search results that have been previously identified as having at least one associated date or location. A timeline or map is displayed that visually represents the distribution of the dates or locations within the results. The timeline is displayed with a histogram graph corresponding to the number of dates in the search results at points along the timeline. The map is displayed with markers at the locations corresponding to the locations in the search results. The user can navigate the result set using the displayed timeline or map.

Abstract: At least one aspect of the present disclosure is directed to systems and methods of generating on-device content items to improve security and network utilization. A client device can access content resources and category information from a data structure in the memory the memory of the client device. The client device can generate on-device content items based on the content resources and the category information. The client device can receive an indication to display a content item in an application executing on the client device. The client device can scan the client device for context information to create a relevant device context. The client device can select an on-device content item based on the relevant device context. The client device can provide the selected on-device item to the application for display, detect an interaction with the displayed content item, and update a content selection model or a content generation model.

Abstract: Methods, systems, and apparatus for receiving a query image, receiving one or more entities that are associated with the query image, identifying, for one or more of the entities, one or more candidate search queries that are pre-associated with the one or more entities, generating a respective relevance score for each of the candidate search queries, selecting, as a representative search query for the query image, a particular candidate search query based at least on the generated respective relevance scores and providing the representative search query for output in response to receiving the query image.

Abstract: Systems and methods are provided for a personalized entity repository. For example, a computing device comprises a personalized entity repository having fixed sets of entities from an entity repository stored at a server, a processor, and memory storing instructions that cause the computing device to identify fixed sets of entities that are relevant to a user based on context associated with the computing device, rank the fixed sets by relevancy, and update the personalized entity repository using selected sets determined based on the rank and on set usage parameters applicable to the user. In another example, a method includes generating fixed sets of entities from an entity repository, including location-based sets and topic-based sets, and providing a subset of the fixed sets to a client, the client requesting the subset based on the client's location and on items identified in content generated for display on the client.

Abstract: Systems and methods are shown for providing private local sponsored content selection and improving intelligence models through distribution among mobile devices. This allows greater data gathering capabilities through the use of the sensors of the mobile devices as well as data stored on data storage components of the mobile devices to create predicted models while offering better opportunities to preserve privacy. Locally stored profiles comprising machine intelligence models may also be used to determine the relevance of the data gathered and in improving an aggregated model for identifying the relevance of data and the selection of sponsored content items. Distributed optimization is used in conjunction with privacy techniques to create the improved machine intelligence models. Publishers may also benefit from the improved privacy by protecting the statistics of type or volume of sponsored content items shown with publisher content.

Abstract: Implementations provide an improved drag-and-drop operation on a mobile device. For example, a method includes identifying a drag area in a user interface of a first mobile application in response to a drag command and receiving a drop location in a second mobile application that differs from the first mobile application. The method may also include determining that a drop location is a text input control and the drag area is not text-based, performing a search for a text description of the drag area, and pasting the text description into the text input control. The method may also include determining that a drop location is an image input control and that the drag area is text based, performing a search using the drag area for a responsive image, and pasting the responsive image into the image input control.

Abstract: Implementations of the present disclosure include actions of receiving image data of an image capturing a scene, receiving data describing one or more entities determined from the scene, the one or more entities being determined from the scene, determining one or more actions based on the one or more entities, each action being provided at least partly based on search results from searching the one or more entities, and providing instructions to display an action interface comprising one or more action elements, each action element being to induce execution of a respective action, the action interface being displayed in a viewfinder

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, relating to on-device query annotating. In some implementations, a search query is received, and a mobile device identifies a reference to a particular entity and a reference to a category based on the query. A model that is stored on the mobile device and stores one or more facts that are associated with one or more entities is accessed. A subset of facts from among the facts that are stored in the model for the particular entity is selected. The search query is annotated based at least on one or more facts of the subset of facts that are stored in the model for the particular entity. The annotated search query is transmitted, from the mobile device to a search engine, for processing. A result of processing the annotated search query is received by the mobile device.

Abstract: Systems and methods are shown for providing private local sponsored content selection and improving intelligence models through distribution among mobile devices. This allows greater data gathering capabilities through the use of the sensors of the mobile devices as well as data stored on data storage components of the mobile devices to create predicted models while offering better opportunities to preserve privacy. Locally stored profiles comprising machine intelligence models may also be used to determine the relevance of the data gathered and in improving an aggregated model for identifying the relevance of data and the selection of sponsored content items. Distributed optimization is used in conjunction with privacy techniques to create the improved machine intelligence models. Publishers may also benefit from the improved privacy by protecting the statistics of type or volume of sponsored content items shown with publisher content.

Abstract: Systems and methods are provided for a personalized entity repository. For example, a computing device comprises a personalized entity repository having fixed sets of entities from an entity repository stored at a server, a processor, and memory storing instructions that cause the computing device to identify fixed sets of entities that are relevant to a user based on context associated with the computing device, rank the fixed sets by relevancy, and update the personalized entity repository using selected sets determined based on the rank and on set usage parameters applicable to the user. In another example, a method includes generating fixed sets of entities from an entity repository, including location-based sets and topic-based sets, and providing a subset of the fixed sets to a client, the client requesting the subset based on the client's location and on items identified in content generated for display on the client.

Abstract: Implementations of the present disclosure include actions of receiving image data of an image capturing a scene, receiving data describing one or more entities determined from the scene, the one or more entities being determined from the scene, determining one or more actions based on the one or more entities, each action being provided at least partly based on search results from searching the one or more entities, and providing instructions to display an action interface comprising one or more action elements, each action element being to induce execution of a respective action, the action interface being displayed in a viewfinder.

Abstract: A system and method of identifying objects is provided. In one aspect, the system and method includes a hand-held device with a display, camera and processor. As the camera captures images and displays them on the display, the processor compares the information retrieved in connection with one image with information retrieved in connection with subsequent images. The processor uses the result of such comparison to determine the object that is likely to be of greatest interest to the user. The display simultaneously displays the images the images as they are captured, the location of the object in an image, and information retrieved for the object.

Abstract: Systems and methods are provided for suggesting actions for selected text based on content displayed on a mobile device. An example method can include converting a selection made via a display device into a query, providing the query to an action suggestion model that is trained to predict an action given a query, each action being associated with a mobile application, receiving one or more predicted actions, and initiating display of the one or more predicted actions on the display device. Another example method can include identifying, from search records, queries where a website is highly ranked, the website being one of a plurality of websites in a mapping of websites to mobile applications. The method can also include generating positive training examples for an action suggestion model from the identified queries, and training the action suggestion model using the positive training examples.

Abstract: Systems and methods are provided for sharing a screen from a mobile device. For example, a method includes receiving, at a second mobile device, an image of a screen captured from a first mobile device and determining whether to trigger an automated action. The method may also include displaying, responsive to not triggering the automated action, annotation data generated for the image with the image on a display of the second mobile device, the annotation data including at least one visual cue corresponding to content in the image relevant to a user of the second mobile device. The method may further include, responsive to triggering the automated action, determining that a mobile application associated with the image is installed on the second mobile device and replaying user input actions received with the image on the second mobile device starting from a reference screen associated with the mobile application.

Abstract: Systems and methods are provided for suggesting actions for selected text based on content displayed on a mobile device. An example method can include converting a selection made via a display device into a query, providing the query to an action suggestion model that is trained to predict an action given a query, each action being associated with a mobile application, receiving one or more predicted actions, and initiating display of the one or more predicted actions on the display device. Another example method can include identifying, from search records, queries where a website is highly ranked, the website being one of a plurality of websites in a mapping of websites to mobile applications. The method can also include generating positive training examples for an action suggestion model from the identified queries, and training the action suggestion model using the positive training examples.

Abstract: A system and method of identifying objects is provided. In one aspect, the system and method includes a hand-held device with a display, camera and processor. As the camera captures images and displays them on the display, the processor compares the information retrieved in connection with one image with information retrieved in connection with subsequent images. The processor uses the result of such comparison to determine the object that is likely to be of greatest interest to the user. The display simultaneously displays the images the images as they are captured, the location of the object in an image, and information retrieved for the object.

Abstract: Systems and methods are provided for a content-based security for computing devices. An example method includes identifying content rendered by a mobile application, the content being rendered during a session, generating feature vectors from the content and determining that the feature vectors do not match a classification model. The method also includes providing, in response to the determination that the feature vectors do not match the classification model, a challenge configured to authenticate a user of the mobile device. Another example method includes determining a computing device is located at a trusted location, capturing information from a session, the information coming from content rendered by a mobile application during the session, generating feature vectors for the session, and repeating this until a training criteria is met. The method also includes training a classification model using the feature vectors and authenticating a user of the device using the trained classification model.