Paypal, Inc.

Kevin Ward

Vijeyta Aggarwal

Michael Charles Todasco

Larry Lingjer Wang

Mayank Chaudhary

Nischitha Thimmappa Gowda Sundaramma

Fransisco Kurniadi

Dinesh Kumar

Prashant Gaurav

Tao Sun

Yue Xin

Krishnakumar Govindarajalu

Yuanyuan Pan

Kimberly Kidney

Systems, methods, and non-transitory computer readable media for visualizing user spending data in an altered reality are provided. Spending data includes items purchased, budgets for specific rooms or categories, prices paid, dates of purchase, and amounts spent. The user may interact within the altered reality to manage spending and move budgets between rooms or categories.

Visualization of spending data in an altered reality

Various systems, mediums, and methods may involve a provider application configured to access a user account associated with a provider server. For example, a system may perform operations to identify one or more other applications installed on the mobile device that may be configured to communicate with the provider server. The system may determine data required by the other applications to perform one or more data transfers with the user account. The system may cause the provider application to send the data required to the other applications. As such, the other applications may be enabled to perform one or more data transfers with the user account based on the data sent to the other applications.

Mobile application configurations to enable data transfers

Aspects of the present disclosure involve systems, methods, devices, and the like for presenting a recommendation. In one embodiment, a system is introduced that includes a plurality of models for obtaining a recommendation score. The recommendation score may be obtained using one or more models which can include supervised and unsupervised learning as well as a combination of user information and transactions. In another embodiment, the system is introduced that can provide a total recommendation score and recommendation generated by an ensemble model whose input can include the one or more recommendation scores previously obtained.

System and method for obtaining recommendations using scalable cross-domain collaborative filtering

Aspects of the present disclosure involve systems, methods, devices, and the like for presenting a recommendation. In one embodiment, a system is introduced that includes a plurality of models for obtaining a recommendation score. The recommendation score may be obtained using one or more recommendation models and a recommendation made based on the recommendation score determined. In another embodiment, the system is introduced that can re-train the recommendation model based on a feedback received in response to a recommendation made using on the recommendation score obtained.

Various systems, mediums, and methods may determine one or more configurations associated with a provider application. For example, a mobile system may determine a request to install a provider application, possibly based on one or more user inputs received by the mobile system. The mobile system may determine other applications installed on the mobile system. The mobile system may determine one or more configurations of the provider application based on the other applications installed. As such, the mobile system may install the provider application to the mobile system based on the one or more configurations determined.

System configurations to determine user data associated with mobile applications

Systems and methods for managing user data across multiple apps are disclosed. An example method includes, determining that an installation of a first app on a user device is completed; identifying a second app in which a user has been authenticated and has been installed on the user device; obtaining a second set of user information associated with the user from the second app; and configuring a user account of the user in the first app using the second set of user information. In some implementations, identifying the second app is executed in response to determining that the installation of the first app on the user device is completed. In some other implementations, identifying the second app is executed in response to a user selection of the first app after the installation.

Growing community of inventors

Campbell, CA, United States of America

Kevin Ward