Describes a clustering algorithm designed for dynamic data bases and presents an update procedure which maintains an effective document classification without reclustering. The effectiveness of the algorithms is demonstrated for a subset of the Cranfield collection. (Author)

Describes a method of iterative searching that uses local metrical clustering in the formulation of additional searches by producing searchonyms, terms which are synonymous to keywords in the context of a single query. The method was applied to a database containing Hebrew and Aramaic text. Seven references are listed. (FM)

Describes a study conducted on the cystic fibrosis (CF) database, a subset of MEDLINE, that investigated clustering structure and the effectiveness of cluster-based retrieval as a function of the exhaustivity of the uncontrolled subject descriptions. Results are compared to calculations for controlled descriptions based on Medical Subject Headings…

Reports research results into a methodology for determining similarity between queries characterized by Boolean search request formulations and discusses similarity measures for Boolean combinations of index terms. Rationale behind these measures is outlined, and conditions ensuring their equivalence are identified. Results of an experiment…

Describes method of automatic document classification in which documents classed as QA by Library of Congress classification system were clustered at six thresholds by keyword using single link technique. Automatically generated clusters were compared to Library of Congress subclasses, and partial classified hierarchy was formed. Twelve references…