Traditionally hypertexts have been limited in size by the manual effort required to create hypertext links. In addition, large hyper-linked collections may overwhelm users with the range of possible links from any node, only a fraction of which may be appropriate for a given user at any time. This work explores automatic methods of link construction based on feedback from users collected during browsing. A full-text search engine mediates the linking process. Query terms that distinguish well among documents in the database become candidate anchors; links are mediated by passage-based relevance feedback queries. The newspaper metaphor is used to organize the retrieval results.
VOIR, a software prototype that implements these algorithms has been used to browse a 74,500 node (250MB) database of newspaper articles. An experiment has been conducted to test the relative effectiveness of dynamic links and user-specified queries. Experimental results suggest that link-mediated queries are more effective than user-specified queries in retrieving relevant information. The paper concludes with a discussion of possible extensions to the linking algorithms.