There has been increasing interest over the past few years in systems that help users exchange recommendations about World Wide Web documents. Programs have ranged from those that rely totally on user pre-selection, to others that are based on artificial intelligence. This paper proposes a system that falls between these two extremes, providing distinct advantages over other existing systems since it utilizes the structure and attributes associated with Hyperwave documents. This recommender system, which also ensures integrity of external links through its underlying server environment, can enhance the knowledge base of learning associations and other intranet groups. Following an introduction to the context of the project and user participation, the paper briefly describes the features of the Hyperwave server, a document management system for large quantities of multimedia data that can be spread over multiple remote servers. The Simple Recommender System (SRS), prototyped at the University of Auckland (New Zealand), is then detailed, including client-server arrangements and features that support making and receiving recommendations. The issue of maintaining referential integrity within a library of recommendations is considered. (Author/AEF)