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: 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: Techniques are disclosed relating to automatically synthesizing user interface (UI) component instances. In disclosed techniques a computer system receives a set of existing UI elements and a set of design rules for the set of existing elements, where design rules in the set of design rules indicate one or more allowed states for respective UI elements in the set of existing UI elements. The one or more allowed states may correspond to one or more visual characteristics. Using the set of existing UI elements, the computer system may then automatically generate a plurality of UI component instances based on the set of design rules, where a respective UI component instance includes a first UI element in a first allowed state. The computer system may then train, using the plurality of UI component instances, a machine learning model operable to automatically generate UI designs.

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 identifying duplicate coding and/or design used in different parts of a user interface (e.g., a web application). In some embodiments, a plurality of visible elements of an interface are detected based on hierarchical user interface code. In some embodiments, a device groups sets of the plurality of visible elements based on determined coordinates and depth levels for the detected elements. In some embodiments, groups that meet a threshold similarity criterion are identified. In some embodiments the threshold similarity criterion is based on classification of detected elements and/or geospatial analysis.

Abstract: Techniques are disclosed relating to grouping user interface elements into components. The disclosed techniques may include, for example, determining, based on hierarchical user interface code, a plurality of visible elements of a graphical user interface. In addition, the disclosed techniques include determining coordinates for bounding boxes for ones of the plurality of visible elements and determining depths within the hierarchical user interface code for the plurality of visible elements. The disclosed techniques include generating groupings for the plurality of visible elements using unsupervised clustering and the determined coordinates and depths and storing information specifying the generated groupings.

Abstract: Techniques are disclosed relating to providing customized user interfaces to different groups of users. A computing system may determine a plurality of different design types for a user interface and cause display of user interfaces that exhibit the different design types to different users. Based on user interactions with the user interfaces, the system may generate one or more metrics. The system may and may determine attribute values for attributes of users who interact with the user interface. The system may perform one or more correlation procedures to correlate the attribute values with one or more of the metrics. In disclosed embodiments, the computing system generates groups of users based on the correlation. The computing system may assign at least one of the design types to at least one of the groups of users based on the correlation.

Abstract: Disclosed techniques relate to customization of user interface designs based on user input that specifies high-level design properties. In some embodiments, a system displays a user interface in a user interface customization program. In some embodiments, based on user input via a customization interface element that specifies a direction or change for a design property, the system performs an adjustment to formatting parameters for the user interface, where the user input does not explicitly specify the adjustment to the formatting parameters. The system may display an adjusted user interface that exhibits the adjusted formatting parameters.

Abstract: Disclosed herein are system, method, and computer program product embodiments for automatically upgrading and finding components similar to legacy versions. In an embodiment, an automatic upgrading system determines one or more properties of a first web part and identifies a first attribute for the one or more properties of the first web part. A second web part is identified by similar attribute as the first web part to creat a web page by adding at least the second web part to the web page.

Abstract: Disclosed techniques relate to scoring input elements independently, based on user comparison inputs for training data. In some embodiments, for a set of training elements, a system displays subsets to users and receives user input indicating ones of the subsets that more strongly exhibit a specified user interface design parameter relative to other user interface elements in that subset. In some embodiments, a ranking technique such as Bradley-Terry techniques generate a ranking of the user interface elements according to the design parameter based on the user input. In some embodiments, the system trains a machine learning engine to score a subsequently presented input user interface element according to the design parameter, using outputs of the ranking as labels.

Abstract: Techniques are disclosed relating to emphasizing user interface elements for different users based on user attributes. In some embodiments, a system maintains a set of information (e.g., for a particular product) that includes multiple types of information. The system may access the same set of information for different user requests. The computing system may determine first and second subsets of the set of information based on attributes of the different users. The computing system may cause display of a first user interface on a device of the first user, where the first user interface shows only the first subset of information with a first element displayed using a first format. The computing system may cause display of a second user interface on a device of the second user, where the second user interface shows only the second subset of information with the first element displayed using a second format.

Abstract: Techniques are disclosed relating to custom user interface design based on user interaction metrics from another communication channel. In disclosed embodiments, a computing system generates one or more interaction metrics, based on a first set of user input characteristics for user interaction with multiple different user interface formats via a first communication channel. In some embodiments, the first communication channel supports tracking of the first set of user input characteristics and a second communication channel supports tracking of a second, different set of user input characteristics. In some embodiments, the computing system determines, based on the one or more interaction metrics from the first communication channel, a set of design parameters for formatting a user interface to be displayed via the second communication channel.

Abstract: Techniques are disclosed relating to providing customized user interfaces to different groups of users. A computing system may determine a plurality of different design types for a user interface and cause display of user interfaces that exhibit the different design types to different users. Based on user interactions with the user interfaces, the system may generate one or more metrics. The system may and may determine attribute values for attributes of users who interact with the user interface. The system may perform one or more correlation procedures to correlate the attribute values with one or more of the metrics. In disclosed embodiments, the computing system generates groups of users based on the correlation. The computing system may assign at least one of the design types to at least one of the groups of users based on the correlation.

Abstract: Disclosed herein are system, method, and computer program product embodiments for automatically upgrading and finding components similar to legacy versions. In an embodiment, an automatic upgrading system may determine a first pattern for a first graphical component of a computing platform, identify a first attribute for the first pattern. A second graphical component may be searched by similar attribute as the first graphical component to replace the first graphical component for the computing platform.

Abstract: Techniques are disclosed relating to refining, based on user feedback, one or more machine learning engines for automatically generating component-based user interfaces. In various embodiments, a computer system stores template information that defines a plurality of component types and one or more display parameters identified for one or more user interfaces. The computer system may receive a request to generate a user interface, where the request specifies a data set to be displayed. Further, the computer system may automatically generate a user interface, where the generating is performed by one or more machine learning engines that use the template information and the data set as inputs. The computer system may then provide the user interface to one or more users, receive user feedback associated with the user interface, and train at least one of the one or more machine learning engines based on the user feedback.

Abstract: Techniques are disclosed relating to grouping user interface elements into components. The disclosed techniques may include, for example, determining, based on hierarchical user interface code, a plurality of visible elements of a graphical user interface. In addition, the disclosed techniques include determining coordinates for bounding boxes for ones of the plurality of visible elements and determining depths within the hierarchical user interface code for the plurality of visible elements. The disclosed techniques include generating groupings for the plurality of visible elements using unsupervised clustering and the determined coordinates and depths and storing information specifying the generated groupings.

Abstract: Techniques are disclosed relating to identifying duplicate coding and/or design used in different parts of a user interface (e.g., a web application). In some embodiments, a plurality of visible elements of an interface are detected based on hierarchical user interface code. In some embodiments, a device groups sets of the plurality of visible elements based on determined coordinates and depth levels for the detected elements. In some embodiments, groups that meet a threshold similarity criterion are identified. In some embodiments the threshold similarity criterion is based on classification of detected elements and/or geospatial analysis.

Abstract: Techniques are disclosed relating to automatically generating user interfaces. In some embodiments, input data to be displayed is grouped into components (e.g., based on depth within hierarchical code, coordinates in a display space, etc.). These components may be based on template information that defines a set of known component types. In some embodiments, the system formats the selected components according to display parameters and causes display of a user interface that displays the components based on the formatting. In various embodiments, the disclosed techniques may allow automatic creation of effective user interfaces without information specifying layout and formatting for input data. This may provide flexible, quality interfaces without requiring design or coding expertise. Further, disclosed techniques may allow the automatic interface generator to generate interfaces similar to other existing interfaces.

Abstract: Techniques are disclosed relating to predicting events based on automation parameters and initiating a procedure to request user input. In some embodiments, the system automatically selects one or more component types to display an interface to request the user input, e.g., based on user interface elements associated with the procedure. These component-based techniques may be used to imitate another interface while automatically formatting the input data without a known template.