VISAR: a system for inference and navigation of hypertext

Hypertext systems have traditionally been constructed by hand. This process can stand improvement in several aspects: it is laborious; requires a human to understand the text and infer all the relationships between the concepts/topics; and while the resulting hypertext may be traversed by a reader in an arbitrary fashion, s/he may still find it difficult to understand the concepts as expressed by the builder of the hypertext. We present a knowledge-intensive assistant for building hypertext fragments from a knowledge base customised both explicitly and implicitly by a user. Such a presentation may clarify relationships between concepts that were present implicitly in multiple sources of information. In the domain of an intelligent information retrieval system, we show how such an assistant may render customised views of knowledge extracted in a manageable form. While the presentation medium of the original system is graphic, we also speculate that presentation of the information in alternative hypermedia appears to be straightforward.