This paper describes a method of learning a user's field of interest and the effects of applying this method to information retrieval. This method uses a dynamic word network (DWN) within the framework of an associated information retrieval approach. The associated information retrieval approach aims at retrieving easily, and precisely the information that a user needs out of a database. To do this, the information retrieval system must understand what the user intends to retrieve, that is, the user's interest. An associated information retrieval system (AIRS) that incorporates this approach is now being developed. AIRS learns the user's interest from sample documents and represents the user model as a DWN. A DWN consists of nodes and links. Each node corresponds to a term which AIRS can use for retrieval and each link corresponds to the relationship between two terms. Each node also has a node weight. To evaluate DWN performance, we retrieved information using AIRS comparing the output with conventional methods. The results show how the DWN improves the precision of information retrieval.