Proposes use of parallel computing systems to overcome the computationally intense clustering process. Results show some near linear speed up in higher threshold clustering applications, meeting the requirements to classify, group and process large document sets within nonprohibitive execution times. Includes graphs and charts. (JAK)

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)