Adobe, Inc.

Peter Raymond Fransen

Jen-Chan Jeff Chien

Kevin Gary Smith

Gavin Stuart Peter Miller

Kent Andrew Edmonds

Thomas William Randall Jacobs

Jeffrey Michael Day

Brian David Williams

Matthew William Rozen

Cory Lynn Edwards

Jonathan R Gale

Christine Xuan Phan

Tara V Anand

Andrew H VanWagoner

Sarah Marie Garcia

Andy H VanWagoner

Aaron Motayne

Jacob D Lords

Navigation and reward techniques involving physical goods and services are described. In one example, digital content is configured to aid navigation of a user between different physical goods or services. This navigation includes user specified good or services as well as recommended goods or services that are not specified by the user. In another example, digital content is provided as part of a reward system. In return for permitting access to user data, the user is provided with rewards that are based on this monitored interaction. In this way, an owner of the store may gain detailed knowledge which may be used to increase likelihood of offering goods or services of interest to the user. In return, the user is provided with rewards to permit access to this detailed knowledge.

Navigation and rewards involving physical goods and services

Application personalization techniques and systems are described that leverage an embedded machine learning module to preserve a user's privacy while still supporting rich personalization with improved accuracy and efficiency of use of computational resources over conventional techniques and systems. The machine learning module, for instance, may be embedded as part of an application to execute within a context of the application to learn user preferences to train a model using machine learning. This model is then used within the context of execution of the application to personalize the application, such as control access to digital content, make recommendations, control which items of digital marketing content are exposed to a user via the application, and so on.

Application digital content control using an embedded machine learning module

Digital content control based on shared machine learning properties

In implementations of determining user segmentation based on a photo library, a device maintains digital images in the photo library, as well as metadata associated with the digital images. The device includes a segmentation module implemented to determine characteristics about a user of the device by analysis of the metadata of the digital images. The segmentation module can determine a segmentation based on the characteristics determined about the user. The segmentation includes one or more segments that each represent a generalized aspect of the user, where a generalized aspect is attributable to multiple people and anonymity of the user is maintained. The segmentation module can associate an anonymous identifier with the segmentation effective to maintain the anonymity of the user and privacy of the metadata. The segmentation and the anonymous identifier can then be communicated to a marketing system that generates personalized marketing messages based on the segmentation.

Determining user segmentation based on a photo library

Segment generation describing usage patterns is described. In one or more implementations, user interaction with a browser is monitored to navigate through a plurality of web pages using a computing device. Data is extracted from web documents associated with the plurality of web pages automatically and without user intervention by one or more modules of the computing device, the data usable to describe a usage pattern involving the navigation through the plurality of web pages. A segment is generated which describes the usage pattern automatically and with user intervention, the segment configured to identify the usage pattern to target content.

Segment generation describing usage patterns

Certain embodiments involve determining visual context associated with user behavior and associating the visual context with the user behavior. For example, a system captures a portion of a user interface provided to a user at a time of a user action on the user interface. The captured portion can include digital content and the system can detect the digital content. The system can also generate a digital representation of the digital content. The digital representation can indicate the digital and exclude the digital content. The system can determine a visual context associated with the user action based on the generated digital representation. The visual context describes the digital content displayed via the user interface at the time of the user action. The system can also determine subsequent digital content to output to the user to create a subsequent visual context to encourage a particular user behavior.

Determining and correlating visual context on a user device with user behavior using digital content on the user device

In an example embodiment, user interactions with a software component may be tracked in an efficient manner. Specifically, an analytics tracking request triggered by user interaction with a software component is received. Then a value assigned to the user is retrieved. It is then determined if the value assigned to the user exceeds a value threshold assigned to the analytics tracking request. Based on a comparison between the value assigned to the user and the threshold value, an analytics tracking function associated with the analytics tracking request is launched.

Changing depth of analytics tracking or content targeting based on user value

Marketing data communication control techniques and systems are described. A digital environment is described in which a plurality of devices are configured to communicate marketing data to one or more of a plurality of marketing services. One or more inputs are received that are entered by a user through interaction with the single unified user interface of the computing device, the one or more inputs specifying marketing data communication settings to control communication of marketing data per individual ones of the plurality of devices and per individual ones of the plurality of marketing data collection services. The marketing data communication settings are propagated by the computing device to respective ones of the plurality of devices, the propagated marketing data communication settings configured to control communication of marketing data by the respective said devices to respective ones of the plurality of marketing data collection services.

Marketing data communication control

Facilitating analysis of user interface gesture patterns is described. In example implementations, a computing device acquires data that describes a user interface gesture pattern, such as finger movements on a touchscreen, in terms of pixels of a visual display. A repetitive arrangement of polygons, such as a grid of rectangles, is logically overlaid on the visual display. The computing device transforms the pixel-based data into polygon-based data that represents the gesture pattern in terms of polygons traversed by the gesture pattern. The computing device also converts the polygon-based data into text-based data such that the gesture pattern is represented by textual characters, such as a text string. The text string can include, for instance, a list of polygons traversed by the gesture pattern. The text-based data is forwarded to a service that can efficiently analyze relationships that may exist among multiple gesture patterns across multiple devices or end users.

Facilitating analysis of use interface gesture patterns

Systems and methods for accurately and efficiently associating devices with a user profile and compiling use information from such devices are disclosed. Devices are associated with the same user profile based on identifying consistent proximity of the devices to one another, e.g., by identifying that the devices are frequently used in proximate locations during a time period or by identifying that the devices are paired with one another. Local devices, rather than a remote server, are used to more efficiently associate devices with the user profile and/or compile use information from such devices. Devices that are associated with the same user profile as a local collection device send use information to the local collection device. The information from all of the devices associated with the user profile is then shared locally with other devices associated with that user profile and sent to a remote collection server.

Techniques for associating and sharing data from multiple local devices

Facilitating location-aware analysis is described. In some embodiments, a database building module is configured to build a point of interest (POI) database based on a tree data structure that includes multiple nodes respectively corresponding to multiple areas. The database building module includes a content node processing module that inserts an entry in the POI database having a content field populated by a POI descriptor included with a content node. The database building module also includes a reference node processing module that inserts an entry having multiple reference fields respectively populated with area indicators corresponding to multiple subnodes of a reference node. In other embodiments, a POI database search module is configured to search a POI database to ascertain multiple POIs with regard to a location of a computing device. The search module searches key fields of reference entries and content entries using an area indicator matching the computing device's location.

Facilitating location-aware analysis

The environment within which IoT devices are operating is determining based on sets of fingerprints collected from the IoT devices. The set of fingerprints for each respective IoT device contains at least one fingerprint corresponding to a sensed IoT device in communication with the respective IoT device. A similarity score is generated for pairs of IoT devices by comparing their respective sets of fingerprints to identify matching fingerprints. The IoT devices are grouped into a common environment based on the similarity scores. In some embodiments, content is provided over one or more communications networks to a user associated with an IoT device based on the IoT device being grouped into the common environment with one or more other IoT devices.

Growing community of inventors

Soquel, CA, United States of America

Peter Raymond Fransen