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: Embodiments described herein provide a workflow visualization tracking tool based on text mining on a conversation channel. Specifically, a communication interface receives a plurality of user activity items that are related to a shared work item among the plurality of tenants. A first sequence of status indicators representing a workflow progress of the shared work item over a plurality of time instances may be generated from the plurality of user activity items. A first subset of the plurality of user activity items are determined, which are related to at least one sub-item reflected in the first sequence of status indicators. A second sequence of status indicators representing a second workflow progress of the at least one sub-item over the plurality of time instances may be generated from the first subset of the user activity items. The first sequence of status indicators and the second sequence of status indicators may be presented in a visualization structure via a user interface.

Abstract: A method receives an input file. The input file includes a plurality of entries where different entries are associated with a different characteristic. A selection of a guide for an entry is determined where a guide includes guidelines for formatting content in an entry in the plurality of entries. The method performs analyzing an image from the entry to generate image variations. Then, the method analyzes the image and the image variations to place text items from the entry in the image and the image variations where the text items in the image and the image variations are formatted based on the guidelines in the guide for the entry. A plurality of design variants is generated for the entry based on the image and the image variations that include text items.

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 are database systems, computing devices, methods, and computer program products for identifying recurring sequences of user interactions with an application. In some implementations, a server of a database system provides a user interface of the application for display at a computing device. The database system stores data objects identifying a first plurality of user interactions with the application. The server receives information representing a second plurality of user interactions with the application. The server updates the database system to further identify the second user interactions. The server identifies a recurring sequence of user interactions from the first and second user interactions as resulting in a first target state of the application. The server updates the database system to associate the recurring sequence of user interactions with the first target state of the application.

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: Embodiments described herein provide a contextual conversation summarization mechanism on a chat platform. Specifically, a communication interface receives a first conversation line originated from a first user and a second conversation line originated from a second user. The mechanism then determines that the first conversational line and the second conversational line belong to a same conversation channel based on a channel indicator. The first conversation line and the second conversation line are concatenated as an input to a summarization model. The summarization model then generates a summary of the conversation channel associated with a timestamp. A first visualization element representing a first conversation contribution by the first user and a second visualization element representing a second conversation contribution by the second user are generated based on the generated summary.

Abstract: A method for data processing is described. The method includes receiving, from a client of a web service, a request for a web component included in a web page supported by the web service, where the web component is associated with a data structure that defines design characteristics of the web component. The method further includes determining configuration parameters that define stylistic characteristics of the web component based on data attributes of the web page and the data structure associated with the web component, where the configuration parameters are determined using a model trained on a corpus of web pages supported by the web service. The method further includes transmitting, to the client and in response to the request, an indication of the configuration parameters for the web component, where the indication is configured to display the web component according to the stylistic characteristics defined by the configuration parameters.

Abstract: Embodiments described herein provide a workflow visualization tracking tool based on text mining on a conversation channel. Specifically, a communication interface receives a plurality of user activity items that are related to a shared work item among the plurality of tenants. A first sequence of status indicators representing a workflow progress of the shared work item over a plurality of time instances may be generated from the plurality of user activity items. A first subset of the plurality of user activity items are determined, which are related to at least one sub-item reflected in the first sequence of status indicators. A second sequence of status indicators representing a second workflow progress of the at least one sub-item over the plurality of time instances may be generated from the first subset of the user activity items. The first sequence of status indicators and the second sequence of status indicators may be presented in a visualization structure via a user interface.

Abstract: Disclosed are database systems, computing devices, methods, and computer program products for identifying recurring sequences of user interactions with an application. In some implementations, a server of a database system provides a user interface of the application for display at a computing device. The database system stores data objects identifying a first plurality of user interactions with the application. The server receives information representing a second plurality of user interactions with the application. The server updates the database system to further identify the second user interactions. The server identifies a recurring sequence of user interactions from the first and second user interactions as resulting in a first target state of the application. The server updates the database system to associate the recurring sequence of user interactions with the first target state of the application.

Abstract: Systems, devices, and techniques are disclosed for conversation topic extraction. Text of a communication channel may be received. The text of the communication channel may be divided into conversation documents based on conversation threads of the communication channel. Phrases of the text of the conversation documents may be tokenizes. Topic phrases for the conversation documents may be determined by assigning importance scores to the tokenized phrases using unsupervised topic extraction. The topic phrases may be the tokenized phrases with the highest importance scores.

Abstract: Systems, devices, and techniques are disclosed for visual text summary generation. An input text may be received. Keywords may be extracted from the input text. Representative keywords may be generated from the keywords. A graph representation of the representative keywords may be generated. Images associated with the representative keywords may be received. A visual-representation style may be selected based on the graph representation of the representative keywords. The mages associated with the representative keywords may be arranged according to the selected visual-representation style and the graph representation of the representative keywords.

Abstract: Systems, devices, and techniques are disclosed for style-based dynamic content generation. A seed image, entity design data, entity style data, and text items may be received. Bounding boxes that identify areas of the seed image for the placement of the text items may be generated for the seed image. Variant images may be generated from the seed image, the entity design data, and the entity style data. The variant images may be generated by placing text items in the bounding boxes based on the entity design data and rendering text of the text items using the entity style data.

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: 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: 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.