US Patent 10157291 Collection flow for confidential data

In an example embodiment, an attribute interference model is trained by a machine learning algorithm to output missing attribute values from a member profile of a social networking service. In an attribute inference phase, an identification of a member of a social networking service is obtained. A member profile corresponding to the member of the social networking service is retrieved using the identification. The member profile is then passed to the attribute inference model to generate one or more missing attribute values for the member profile. A collection flow, defined in a user interface of a computing device, is modified based on the generated one or more missing attribute values, the collection flow defining a sequence of screens for collecting confidential data. The modified collection flow is then presented to the member in the user interface to collect confidential data from the member.