Abstract: A method includes receiving first event data from a device, the first event data including a first identifier (ID) that identifies the device, web browser metadata, and data associated with an application state. The method includes generating a first persona including the first ID and a first event identifier that identifies a first user action. The method includes receiving second event data, the second event data including device metadata and a second ID that identifies the device. The method includes generating a second persona based on the second event data, the second persona including the second ID and a second event identifier that identifies a second user action. Additionally, the method includes determining that the first and second personas are associated with the device based on matches between the browser metadata and device metadata and transmitting a response to the device configured to route the device to the application state.

Abstract: A method includes receiving first event data from a device, the first event data including a first identifier (ID) that identifies the device, web browser metadata, and data associated with an application state. The method includes generating a first persona including the first ID and a first event identifier that identifies a first user action. The method includes receiving second event data, the second event data including device metadata and a second ID that identifies the device. The method includes generating a second persona based on the second event data, the second persona including the second ID and a second event identifier that identifies a second user action. Additionally, the method includes determining that the first and second personas are associated with the device based on matches between the browser metadata and device metadata and transmitting a response to the device configured to route the device to the application state.

Abstract: A method includes receiving first event data from a device, the first event data including a first identifier (ID) that identifies the device, web browser metadata, and data associated with an application state. The method includes generating a first persona including the first ID and a first event identifier that identifies a first user action. The method includes receiving second event data, the second event data including device metadata and a second ID that identifies the device. The method includes generating a second persona based on the second event data, the second persona including the second ID and a second event identifier that identifies a second user action. Additionally, the method includes determining that the first and second personas are associated with the device based on matches between the browser metadata and device metadata and transmitting a response to the device configured to route the device to the application state.

Abstract: A method includes receiving first event data from a device, the first event data including a first identifier (ID) that identifies the device, web browser metadata, and data associated with an application state. The method includes generating a first persona including the first ID and a first event identifier that identifies a first user action. The method includes receiving second event data, the second event data including device metadata and a second ID that identifies the device. The method includes generating a second persona based on the second event data, the second persona including the second ID and a second event identifier that identifies a second user action. Additionally, the method includes determining that the first and second personas are associated with the device based on matches between the browser metadata and device metadata and transmitting a response to the device configured to route the device to the application state.

Abstract: A method includes receiving first event data from a device, the first event data including a first identifier (ID) that identifies the device, web browser metadata, and data associated with an application state. The method includes generating a first persona including the first ID and a first event identifier that identifies a first user action. The method includes receiving second event data, the second event data including device metadata and a second ID that identifies the device. The method includes generating a second persona based on the second event data, the second persona including the second ID and a second event identifier that identifies a second user action. Additionally, the method includes determining that the first and second personas are associated with the device based on matches between the browser metadata and device metadata and transmitting a response to the device configured to route the device to the application state.

Abstract: A method includes receiving first event data from a device, the first event data including a first identifier (ID) that identifies the device, web browser metadata, and data associated with an application state. The method includes generating a first persona including the first ID and a first event identifier that identifies a first user action. The method includes receiving second event data, the second event data including device metadata and a second ID that identifies the device. The method includes generating a second persona based on the second event data, the second persona including the second ID and a second event identifier that identifies a second user action. Additionally, the method includes determining that the first and second personas are associated with the device based on matches between the browser metadata and device metadata and transmitting a response to the device configured to route the device to the application state.

Abstract: A method includes receiving first event data from a device, the first event data including a first identifier (ID) that identifies the device, web browser metadata, and data associated with an application state. The method includes generating a first persona including the first ID and a first event identifier that identifies a first user action. The method includes receiving second event data, the second event data including device metadata and a second ID that identifies the device. The method includes generating a second persona based on the second event data, the second persona including the second ID and a second event identifier that identifies a second user action. Additionally, the method includes determining that the first and second personas are associated with the device based on matches between the browser metadata and device metadata and transmitting a response to the device configured to route the device to the application state.

Abstract: Systems, methods, and non-transitory computer-readable media can collect past user information and churn data for a plurality of users. A churn prediction model is trained using the past user information and churn data. A churn propensity score is calculated for a present user based on the churn prediction model, the churn propensity score indicative of the likelihood of the present user to churn.

Abstract: Systems, methods, and non-transitory computer-readable media can acquire an image that depicts at least one character. A set of pixels, within the image, through which the at least one character is depicted can be identified. At least one linear portion, within the image, can be identified based on the set of pixels. For each sub-portion within the at least one linear portion, a respective first confidence score representing a respective first likelihood that a respective sub-portion depicts the at least one character can be determined.

Abstract: A method includes receiving first event data from a device, the first event data including a first identifier (ID) that identifies the device, web browser metadata, and data associated with an application state. The method includes generating a first persona including the first ID and a first event identifier that identifies a first user action. The method includes receiving second event data, the second event data including device metadata and a second ID that identifies the device. The method includes generating a second persona based on the second event data, the second persona including the second ID and a second event identifier that identifies a second user action. Additionally, the method includes determining that the first and second personas are associated with the device based on matches between the browser metadata and device metadata and transmitting a response to the device configured to route the device to the application state.

Abstract: Systems, methods, and non-transitory computer-readable media can acquire an image that depicts at least one character. A set of pixels, within the image, through which the at least one character is depicted can be identified. At least one linear portion, within the image, can be identified based on the set of pixels. For each sub-portion within the at least one linear portion, a respective first confidence score representing a respective first likelihood that a respective sub-portion depicts the at least one character can be determined.

Abstract: Systems, methods, and non-transitory computer-readable media can collect past user information and churn data for a plurality of users. A churn prediction model is trained using the past user information and churn data. A churn propensity score is calculated for a present user based on the churn prediction model, the churn propensity score indicative of the likelihood of the present user to churn.

Abstract: At least one embodiment of this disclosure includes a method of inferring attribute labels for a user in a social networking system based on the user's social connections and user-specified attribute labels in the social networking system. The method can include: establishing variational equations based on attribute labels of nodes in an ego network in a social graph of a social networking system; determining likelihood scores for at least a portion of the attribute labels of neighboring nodes from a focal user node in the ego network based on user-specified attribute labels from the social networking system; and calculating probability distributions of possible attribute labels for the focal user node of the ego network based on the variational equations and the likelihood scores.

Abstract: At least one embodiment of this disclosure includes a method of inferring attribute labels for a user in a social networking system based on the user's social connections and user-specified attribute labels in the social networking system. The method can include: establishing variational equations based on attribute labels of nodes in an ego network in a social graph of a social networking system; determining likelihood scores for at least a portion of the attribute labels of neighboring nodes from a focal user node in the ego network based on user-specified attribute labels from the social networking system; and calculating probability distributions of possible attribute labels for the focal user node of the ego network based on the variational equations and the likelihood scores.

Abstract: At least one embodiment of this disclosure includes a method of inferring attribute labels for a user in a social networking system based on the user's social connections and user-specified attribute labels in the social networking system. The method can include: establishing variational equations based on attribute labels of nodes in an ego network in a social graph of a social networking system; determining likelihood scores for at least a portion of the attribute labels of neighboring nodes from a focal user node in the ego network based on user-specified attribute labels from the social networking system; and calculating probability distributions of possible attribute labels for the focal user node of the ego network based on the variational equations and the likelihood scores.