Search is becoming more interactive, and query logs are the commonly used resources to propose search suggestions. An alternative to exploiting query logs can be an extraction of a domain model based on actual documents. This is particularly promising when restricting search to an intranet or a Web site where the size of the collection allows the application of full natural language parsing and where the documents can be expected to be virtually spam-free. Using a university Web site as an exemplar, we can automatically extract predicate-argument structures from documents to acquire a domain model. This domain model is a term association graph which can be employed to guide users in information finding. This can be done by locating a user query in the model and suggesting directly connected terms as query suggestions. Alternatively, one could apply various graph-based algorithms to the initial model with a purpose of identifying the best possible suggestions.