Analysis of Search Key Retrieval on a Large Bibliographic File

Abstract

Two search keys (4,5 and 3,3) are aMlyzed using a probability formula on a bibliographic file of 857,725 records. Assuming random requests by record permits the creation of a predictive model which more closely approximates the actual behavior of a search and retrieval system as determined by a usage survey.

Catalog Records Retrieved by Personal Author Using Derived Search Keys

“…5 However, Guthrie and Slifko have shown that random selection of entries, rather than keys, yields results closer to actual experience but with a higher number of entries per reply. 6 For example, they found on retrieving from a file of 857,725 records using a 4, 5 (four characters of main entry, five characters of title) key tl1at when the basis of the search was random keys there was one entry per reply 81.3 percent of the time, but when the basis was random records, there was one entry per reply 55.7 percent of the time.…”

Computer-Based Systems, A New Dimension to Library Cooperation

“…The technique of using truncated search keys to access the computerized catalogs as employed at the Ohio State University libraries and OCLC is an example of a type of catalog searching unfamiliar to many librarians. 5 The prospect of computerized descriptive cataloging pushes the new librarianship a considerable distance from classical librarianship. 6 To make effective decisions in the area of library automation, librarians must know much more about computation than they think they must know.…”

Statistical Behavior of Search Keys

“…Guthrie, in a recent paper, provides a bridge between the two types of research by discussing his findings in terms of two models. 6 One of his models, which asserts that each search key value has an equal chance of being requested, is equivalent to the assumption that g"(p) = 1, and g(p) = f(p). Guthrie finds that this is not an adequate representation of his data.…”