Abstract: Techniques are disclosed relating to determining a similarity of components of a current webpage to different UI components for use in automatically generating an updated webpage. A computer system may receive information specifying a current webpage, including a particular current UI component and information specifying a plurality of different UI components for an updated webpage. The computer system may identify one or more characteristics of the particular current UI component. The computer system may determine, based on the identified one or more characteristics, a similarity of ones of the plurality of different UI components to the particular current UI component. The computer system may select, based on the determining, a particular different UI component from the plurality of different UI components for use, in the updated webpage, for the particular current UI component. Such techniques may advantageously improve user experience by automatically providing up-to-date user interfaces.

Abstract: Techniques are disclosed for automatically generating new content using a trained 1-to-N generative adversarial network (GAN) model. In disclosed techniques, a computer system receives, from a computing device, a request for newly-generated content, where the request includes current content. The computer system automatically generates, using the trained 1-to-N GAN model, N different versions of new content, where a given version of new content is automatically generated based on the current content and one of N different style codes, where the value of N is at least two. After generating the N different versions of new content, the computer system transmits them to the computing device. The disclosed techniques may advantageously automate a content generation process, thereby saving time and computing resources via execution of the 1-to-N GAN machine learning model.

Abstract: Disclosed herein are system, method, and computer program product embodiments for determining a user-preferred feature type. An embodiment operates by maintaining user-presented features associated with user-presented records, wherein the user-presented features comprise one or more user-presented feature types. After receiving a user-desired feature of the user-presented features, a user-preferred feature type of the user-presented feature types is determined based on the user-presented features and the user-desired feature. Thereafter, a new record and associated feature are to be presented with the new feature being of the user-preferred type.

Abstract: Disclosed herein are system, method and computer readable storage medium for detecting space suitable for overlaying media content onto an image. The system receives a candidate image which may be an image or a video frame. The candidate image is then input into a neural network. The neural network may output coordinates and one or more dimensions representing one or more bounding boxes for inserting media content into the candidate image. The one or more bounding boxes may be transmitted with a request for a media content item to be displayed in a bounding box. In response to the request the media content item may be received, and the candidate image and the media content item overlaid on top of the candidate image within the bounding box may be displayed.

Abstract: Techniques are disclosed for automatically converting a layout image to a text-based representation. In the disclosed techniques, a server computer system receives a layout image that includes a plurality of portions representing a plurality of user interface (UI) elements included in a UI design. The server computer system transforms, via executed of a trained residual neural network (ResNet), the layout image to a text-based representation of the layout image that specifies coordinates of bounding regions of the plurality of UI elements included in the UI design, where the text-based representation is usable to generate program code executable to render the UI design. The disclosed techniques may advantageously automate one or more portions of a UI design process and, as a result save time and computing resources via the execution of an image to text-based conversion ResNet machine learning model.

Abstract: Techniques are disclosed for automatically generating new content using a trained 1-to-N generative adversarial network (GAN) model. In disclosed techniques, a computer system receives, from a computing device, a request for newly-generated content, where the request includes current content. The computer system automatically generates, using the trained 1-to-N GAN model, N different versions of new content, where a given version of new content is automatically generated based on the current content and one of N different style codes, where the value of N is at least two. After generating the N different versions of new content, the computer system transmits them to the computing device. The disclosed techniques may advantageously automate a content generation process, thereby saving time and computing resources via execution of the 1-to-N GAN machine learning model.

Abstract: A textual properties model is used to infer values for certain font properties of interest given certain text-related data, such as rendered text images. The model may be used for numerous purposes, such as aiding with document layout, identifying font families that are similar to a given font families, and generating new font families with specific desired properties. In some embodiments, the model is trained from a combination of synthetic data that is labeled with values for the font properties of interest, and partially-labeled data from existing “real-world” documents.

Abstract: Disclosed herein are system, method, and computer program product embodiments for determining a user-preferred feature type. An embodiment operates by maintaining user-presented features associated with user-presented records, wherein the user-presented features comprise one or more user-presented feature types. After receiving a user-desired feature of the user-presented features, a user-preferred feature type of the user-presented feature types is determined based on the user-presented features and the user-desired feature. Thereafter, a new record and associated feature are to be presented with the new feature being of the user-preferred type.

Abstract: Techniques are disclosed relating to generating a user interface (UI) migration plan, including intermediate UIs, for migrating from a current UI to a new UI. A computer system may receive information specifying a current UI and a new UI, and identify one or more differences between the current and the new UIs. Based on the differences, the computer system may generate information specifying one or more candidate intermediate UIs. The computer system may score the candidate intermediate UIs relative to a specified set of design criteria. The computer system may determine a UI migration plan that specifies a set of the one or more candidate intermediate UIs that are displayable in order to migrate from the current UI to the new UI, where the set of one or more intermediate UIs is selected based on the scoring. Use of the UI migration plan may advantageously reduce user interaction issues.

Abstract: Disclosed herein are system, method, and computer program product embodiments for determining the minimum set of user interface (UI) elements for a task. One embodiment operates by transmitting UI elements associated with an application to a first computing device operated by a first user and a second computing device operated by a second user. Further, the embodiment includes obtaining data structures corresponding to a first task and a second task and then grouping, using a machine learning model, the data structures into a first cluster corresponding to the first task and a second cluster corresponding to the second task. Further still, the embodiment also includes determining a minimum set of UI elements required for the first task based on the first cluster.

Abstract: Disclosed herein are system, method, and computer program product embodiments for determining a user-preferred attribute type. An embodiment operates by maintaining user-presented attributes associated with user-presented records, wherein the user-presented attributes comprise one or more user-presented attribute types. After receiving a user-desired attribute of the user-presented attributes, a user-preferred attribute type of the user-presented attribute types is determined based on the user-presented attributes and the user-desired attribute. Thereafter, a new record and associated attribute are to be presented with the new attribute being of the user-preferred type.

Abstract: Techniques are disclosed relating to measuring presentation aspects of portions of a user interface (UI) that have been identified to be presented neutrally and automatically generating a new UI that reduces differences in the presentation aspects of the identified portions. Portions of the UI identified to be presented neutrally may include elements or content in the UI identified to be presented neutrally. Portions for neutral presentation may include portions of UI that, for example, portions that present legal decisions, portions with survey data, forms or information displays, or portions where a user is requested to make a choice between alternative options. Presentation aspects that may be measured include, for example, visual aspects, clarity aspects, or tonal aspects. Reducing the differences in the presentation aspects may present the elements or content with more neutrality to reduce influence in decisions due to visual, clarity, or tonal aspects between the elements or content.

Abstract: Techniques are disclosed relating to determining locations of child elements in a user interface (UI), automatically updating the locations of the child elements in the UI, and generating an updated UI with the updated locations. A computer system may receive information specifying content of the UI and render an image of the UI based on the received information. Computer vision algorithms may be applied to the rendered of the UI to determine locations of elements in the UI. The locations of the elements may be updated to position the elements in selected locations relative to each other. The updated locations of the elements as determined by the computer vision algorithms may be implemented to generate updating information specifying content for the updated UI.

Abstract: Disclosed herein are system, method, and computer program product embodiments for generating custom user interfaces (UIs) for completing a task. One embodiment operates by obtaining contextual information associated with a user and an application on a user device operated by the user, where the application includes a plurality of UI elements. Then, determining the user is attempting to complete a first task within the application based on the contextual information and a prediction model. The embodiment further operates by obtaining a minimum set of UI elements required for the first task. Further, the embodiment operates by transmitting a first custom UI including the minimum set of UI elements for the first task to the user device for display to the user.

Abstract: Disclosed herein are system, method and computer readable storage medium for detecting space suitable for overlaying media content onto an image. The system receives a candidate image which may be an image or a video frame. The candidate image is then input into a neural network. The neural network may output coordinates and one or more dimensions representing one or more bounding boxes for inserting media content into the candidate image. The one or more bounding boxes may be transmitted with a request for a media content item to be displayed in a bounding box. In response to the request the media content item may be received, and the candidate image and the media content item overlaid on top of the candidate image within the bounding box may be displayed.

Abstract: Techniques are disclosed relating to determining a similarity of components of a current webpage to different UI components for use in automatically generating an updated webpage. A computer system may receive information specifying a current webpage, including a particular current UI component and information specifying a plurality of different UI components for an updated webpage. The computer system may identify one or more characteristics of the particular current UI component. The computer system may determine, based on the identified one or more characteristics, a similarity of ones of the plurality of different UI components to the particular current UI component. The computer system may select, based on the determining, a particular different UI component from the plurality of different UI components for use, in the updated webpage, for the particular current UI component. Such techniques may advantageously improve user experience by automatically providing up-to-date user interfaces.

Abstract: Techniques are disclosed relating to determining a similarity of components of a current user interface (UI) to new UI components for use in automatically generating a new UI. A computer system may receive information specifying a current UI including a particular current UI component and information specifying a plurality of new UI components for a new UI. The computer system may then identify characteristics of the particular current UI component. Based on these identified characteristics, the computer system may score ones of the plurality of new UI components, where the scoring is performed to determine a similarity to the particular current UI component. The computer system may then select, based on the scores, a particular new UI component from the plurality of new UI components for use, in the new UI, for the particular current UI component. Such techniques may advantageously improve user experience by automatically providing up-to-date user interfaces.

Abstract: A textual properties model is used to infer values for certain font properties of interest given certain text-related data, such as rendered text images. The model may be used for numerous purposes, such as aiding with document layout, identifying font families that are similar to a given font families, and generating new font families with specific desired properties. In some embodiments, the model is trained from a combination of synthetic data that is labeled with values for the font properties of interest, and partially-labeled data from existing “real-world” documents.

Abstract: Techniques are disclosed for automatically generating stencils for content of a user interface (UI) to be rendered. A computer system receives information specifying content of a user interface (UI) to be rendered. Based on this information, the computer system identifies one or more bounding regions of content within the UI, including analyzing metadata and a rendered version of the UI. The computer system then automatically generates, one or more UI stencils based on the identified bounding regions, that are displayable as progress indicators prior to rendering corresponding UI content. Once it has generated the stencils, the computer system stores information specifying the one or more UI stencils for use in the UI. Automatically generating stencils for UIs may advantageously reduce the time gap from development to deployment of these UIs while improving their perceived performance and, by extension, improving user experience.

Abstract: Techniques are disclosed relating to generating a user interface (UI) migration plan, including intermediate UIs, for migrating from a current UI to a new UI. A computer system may receive information specifying a current UI and a new UI, and identify one or more differences between the current and the new UIs. Based on the differences, the computer system may generate information specifying one or more candidate intermediate UIs. The computer system may score the candidate intermediate UIs relative to a specified set of design criteria. The computer system may determine a UI migration plan that specifies a set of the one or more candidate intermediate UIs that are displayable in order to migrate from the current UI to the new UI, where the set of one or more intermediate UIs is selected based on the scoring. Use of the UI migration plan may advantageously reduce user interaction issues.