Document collections do not only contain rich semantic content but also a diverse range of relationships. We propose WordleNet, an approach to supporting effective relationship exploration in document collections. Existing approaches mainly focus on semantic similarity or a single category of relationships. By constructing a general definition of document relationships, our approach enables the flexible and real-time generation of document relationships that may not otherwise occur to human researchers and may give rise to interesting patterns among documents. Multiple novel visual components are integrated in our approach, the effectiveness of which has been verified through a case study, a comparative study, and an eye-tracking experiment.