Discovering non-obvious relations in knowledge systems requires models that go beyond surface similarity. This paper presents an online margin-based learning algorithm that infers a latent matrix of category interactions to uncover hidden connections within Wikipedia’s hyperlink structure. The method efficiently scales to large graphs, revealing how semantic structures and user-generated organization jointly shape information discovery.