A Hypertext system is a text data base where the units of information are interlinked using pointers that the user can follow. We call the pointers explicit links (as opposed to computed or virtual links.) HyTeK provides a set of tools designed to help the user explore the information contained in the system. The information contained in the system is represented using at least one of the three following methods: fragments of full text, explicit links between fragments and a collection of frame-like objects organized in a taxonomy. Explicit links are used to represent discourse relationships between fragments of text. The frame-like objects, called Topics, represent concepts in the domain of the text contained in the fragments. Topics are used to index the fragments for retrieval. The taxonomy of Topics represents some of the relationships between fragments that a traditional Hypertext System would represent using explicit links. HyTeK's query system uses the taxonomy of Topics in order to implement tools that allow the user to retrieve fragments selectively by their contents. A user queries the system by building a set of Topics in an interactive process of reformulation. Query reformulation is supported by a set of tools that allow the user to explore the space of Topics. The relationships between the Topics are used to define a similarity measure which is used to rank the target set of the query. This work describes an automatic indexing scheme, a query system and an extension of the Knowledge Representation (KR) system NIKL (KLONE) that was used in HyTeK to implement the taxonomy of Topics. A prototype of HyTeK was implemented in Common-Lisp in a Symbolics 3645 running Genera 7.2. The system has been extensively tested on several test collections of a total of 1000 fragments of text about AIDS treatments. The results indicate clear advantages over traditional Information Retrieval systems and suggest that the use of a KR system for the implementation of a query module for a Hypertext System is promising.