Introduced are information retrieval strategies based on automatic hierarchic clustering of documents. Cluster-based strategies are shown to be as effective as, and more efficient than, linear associative retrieval. (47 references) (Author/SJ)

Addresses the application of automatic classification methods to the problems associated with computerized document retrieval. Different kinds of classifications are described, and both document and term clustering methods are discussed. References and notes are provided. (Author/JD)

Reports the results of experiments in document clustering using three well-known test collections. (Author)

Describes the use of relevance feedback to select additional search terms and discusses the extraction of these terms from a maximum spanning tree connecting all terms in the index term vocabulary; retrieval effectiveness for different spanning trees is shown to be similar. Eight references are included. (Author/BK)