Adobe, Inc.

Interlego Ag

Allan Morgan Young

Richard Sinn

Thomas T Donahue

Guy Nicholas

Oliver Brdiczka

Richard Pong Nam Sinn

Kyoung Tak Kim

Mike Dooley

Jason Christopher Fabbri

Jakub Plichta

Chun Hao Wang

Neha Gautam

Soren Lund

Alexander Robert Dixon

Gabriel Palma Coelho

Christopher Frederic Haupt

Keenan Villani-Holland

The present disclosure relates to systems, methods, and non-transitory computer-readable media that recommends application features of software applications based on in-application behavior and provides the recommendations within a dynamically updating graphical user interface. For instance, in one or more embodiments, the disclosed systems utilize behavioral signals reflecting the behavior of a user with respect to one or more software applications to recommend application features of the software application(s). For instance, in some cases, the disclosed systems recommend an application feature related to recent activity user, an application feature from a curated recommendation list that has yet to be viewed, and/or an application feature determined via machine learning. In some embodiments, the disclosed systems dynamically update a graphical user interface of a client device in real time as the user utilizes the client device to access and navigate the software application(s) to display these recommendations.

Generating personalized in-application recommendations utilizing in-application behavior and intent

Systems and methods for content management are described. One or more embodiments of the present disclosure order content items based on a selection rule, select a rule-based content item based on the ordering, cluster the content items using an unsupervised learning algorithm to obtain a plurality of content groups, select a custom content item related to the rule-based content item based on the content groups, and display the rule-based content item and the custom content item to a user.

Automated content selection based on multiple surface inputs, behavior and machine learning

Certain embodiments involve automatically controlling modifications to typeface designs. For example, a typeface design application provides a design interface for modifying a design of an input character from a typeface. The typeface design application accesses a machine-learning model that is trained, using multiple training typefaces, to recognize the input character as a reference character. The typeface design application receives, via the design interface, an input modifying the design of the input character. The typeface design application determines that the machine-learning model cannot match the reference character to the input character having a modified design. The typeface design application outputs, via the design interface, an indicator that the input character having the modified design is not recognized as the reference character.

Automatically controlling modifications to typeface designs with machine-learning models

A content manipulation application provides a graphical interface for editing graphical content. The graphical interface includes first and second control elements for performing first and second manipulations of the graphical content. If the first control element is selected, the content management application switches the graphical interface to a trackpad mode. The trackpad mode disables the second control element and thereby prevents the second control element from performing the second manipulation. While the graphical interface is in the trackpad mode, the content management application receives an input in an input area that lacks the first control element and performs the first manipulation of the graphical content responsive to receiving the input. Subsequent to the first manipulation being performed, the graphical interface is switched out of the trackpad mode, thereby enabling the second control element to perform the second manipulation.

Selectively enabling trackpad functionality in graphical interfaces

Embodiments for manipulating an object, such as an image, are described. For example, a content application renders the object and supports multiple manipulation modes. A GUI of the application is available at a touch screen of a computing device. A mapping of standard touch screen gestures and object manipulations are defined for each manipulation mode. One of the modes is a standard manipulation mode that supports standard object manipulations. At least one other mode is a special manipulation mode. In this special mode, the standard user gestures are mapped to application-defined manipulations that are different from the standard object manipulations. Based on a user selection of one of the manipulation modes, the selected mode is activated. While in the activated manipulation mode, a standard user gesture is received and the relevant object manipulation is applied to the object.

Smart multi-touch layout control for mobile devices

Image session identifier techniques are described. In one or more implementations, a request is received to create an image sharing session and a session identifier is generated for the image sharing session that is configured to act as a credential to join the image sharing session as a member. A communication is formed that includes the generated session identifier and that is configured for communication via a network to an originator of the request.

Image session identifier techniques

Systems and methods are disclosed for identifying digital fonts. In particular, in one or more embodiments, the disclosed systems and methods detect a digital font, font characteristics, and a text structure with regard to digital text in an electronic document. Moreover, in one or more embodiments, the disclosed systems and methods utilize the detected font characteristics and text structure to search for complementary digital fonts. In particular, one or more embodiments include systems and methods that generate a search query based on determined font characteristics and/or text structures and utilize the search query to automatically identify, recommend, and provide complementary digital fonts for utilization in the electronic document.

Automatically identifying complementary digital fonts based on digital text in electronic documents

A typeface processing application accesses a character skeleton, which has control points and curves defined by control points, and a character outline surrounding the character skeleton. The typeface processing application computes, for a design parameter of a design application, a graphics control dataset based on a particular control point. Doing so involves identifying a pair of control point positions and a pair of expansions of the character outline, where each position or expansion pair corresponds to a pair of design parameter values. The typeface processing application generates the graphics control dataset, which includes intermediate positions of the control point between the pair of positions and intermediate expansions of the character outline between the pair of expansions. The typeface processing application outputs the graphics control dataset to the design application, which can display, responsive to a selection of a design parameter value, modified character designs generated using the graphics control dataset.

Graphics control data for performing skeleton-based modifications of a typeface design

Image session ranking techniques are described. In one or more implementations, indications are received that a plurality of image sharing sessions are available for joining by one or more potential members. The plurality of image sharing sessions are prioritized based on one or more ranking criteria that are usable to determine a relative likelihood that a user wishes to join respective image sharing sessions. A list is formed of suggested image sharing sessions that are arranged, one or another, based on the priority.

Image session ranking

At a service provider, a system receives recipient information containing preferences to be used in an online transaction. The recipient information is received from a client. At the service provider, the system associates the recipient information with the client from which the recipient information was received, and stores the recipient information at the client. The recipient information contains preferences to be used in the online transaction.

Methods and apparatus for maintaining online preferences

The system includes a digital camera or similar CCD or CMOS device which transmits image data to a computing device. Changes such as motion, light or color are detected in various sectors or regions of the image. These changes are evaluated by software which generates output to an audio speaker and/or to an infra-red, radio frequency, or similar transmitter. The transmitter forms a link to a microprocessor based platform which includes remote microprocessor software. Additionally, the platform include mechanical connections upon which a robot can be built and into which the digital camera can be incorporated.

Growing community of inventors

Santa Rosa, CA, United States of America

Allan Morgan Young