The technology disclosed describes systems and methods for generating feature vectors from resource description framework (RDF) graphs. Machine learning tasks frequently operate on vectors of features. Available systems for parsing multiple documents often generate RDF graphs. Once a set of interesting features to be considered has been established, the disclosed technology describes systems and methods for generating feature vectors from the RDF graphs for the documents. In one example setting, a machine learning system can use generated feature vectors to determine how interesting a news article might be, or to learn information-of-interest about a specific subject reported in multiple articles. In another example setting, viable interview candidates for a particular job opening can be identified using feature vectors generated from a resume database, using the disclosed systems and methods for generating feature vectors from RDF graphs.