Demonstrates that the process of comparing each document in an automated system with all others during the classification procedure may be avoided by the use of an inverted file. (FM)

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)

Proposes a means for determining the similarity between search request formulations in online information retrieval systems, and discusses the use of similarity measures for clustering search formulations and document files in such systems. Experimental results using the proposed methods are presented in three tables. A reference list is provided.…

Discussion of clustering of documents and queries in information retrieval systems focuses on the use of a genetic algorithm to adapt subject descriptions so that documents become more effective in matching relevant queries. Various types of clustering are explained, and simulation experiments used to test the genetic algorithm are described. (27…

The exponential growth in the literature of most fields has produced a near crisis situation for the people who provide storage and retrieval facilities for this same literature. One useful tool suggested for anyone interested in mechanizing the process of information storage and retrieval requires that vocabulary used in the system be divided…

Two articles discuss the clustering of composite representations in the Cystic Fibrosis Document Collection from the National Library of Medicine's MEDLINE file. Clustering is evaluated as a function of the exhaustivity of composite representations based on Medical Subject Headings (MeSH) and citation indexes, and evaluation of retrieval…

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…

This study attempts to analyze descriptors taken from subject categories in ERIC thesaurus and used as search terms on CROSS database Bibliographic Retrieval Services. An expectation ratio was computed and cluster analysis was conducted to discover subject relationships among databases. A list of databases retrieved and 12 references are appended.…

These two articles discuss clustering structure in the Cystic Fibrosis Document Collection, which is derived from the National Library of Medicine's MEDLINE file. The exhaustivity of four subject representations and two citation representations is examined, and descriptor-weight thresholds and similarity thresholds are used to compute…

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…

Presents the results of research into the automatic selection of Library of Congress Classification numbers based on the titles and subject headings in MARC records from a test database at the University of California at Berkeley Library School library. Classification clustering and matching techniques are described. (44 references) (LRW)