Abstract: In an example embodiment, a member profile corresponding to a member of a social networking service is obtained. Usage information for the member is then obtained, and one or more member metrics are calculated based on the member profile and usage information for the corresponding member. A plurality of features are extracted from the member profile and the one or more member metrics. The plurality of features is inserted into an organization name confidence score model to obtain a confidence score for an organization name in the member profile.

Abstract: A system and method for generating content based on network source features are provided. In example embodiments, a request for a landing page that shows a display of one or more electronic documents is received. The source of the landing page and the one or more electronic documents is analyzed to determine page view correlation data and selection correlation data. The page view correlation data and selection correlation data is used to generate rank data for the electronic documents. The electronic documents are sorted according to the rank data and a display of the electronic documents in sorted order is provided.

Abstract: In an example embodiment, a member profile corresponding to a member of a social networking service is obtained. Usage information for the member is then obtained, and one or more member metrics are calculated based on the member profile and usage information for the corresponding member. A plurality of features are extracted from the member profile and the one or more member metrics. The plurality of features is inserted into an organization name confidence score model to obtain a confidence score for an organization name in the member profile.

Abstract: A machine may be configured to monitor the quality of software systems based on key performance indicators associated with versions of various units of code. For example, the machine accesses a current version of a unit of code that is not marked as evaluated, in a database. The machine generates a current key performance indicator (KPI) value for the current version of the unit of code based on an execution of the current version of the unit of code. The machine identifies a previous KPI value associated with a previous version of the unit of code that is marked as evaluated, in the database. The machine determines that the current KPI value is less than the previous KPI value and generates an alert for presentation in a user interface of a device. The alert may indicate a decreasing quality level associated with the current version of the unit of code.