On the construction of selection systems
| Pages | 15-28 |
| Date | 01 April 1994 |
| Published date | 01 April 1994 |
| DOI | https://doi.org/10.1108/eb047934 |
| Author | Michael Buckland,Christian Plaunt |
| Subject Matter | Information & knowledge management,Library & information science |
ON
THE CONSTRUCTION OF SELECTION SYSTEMS
Michael Buckland and Christian Plaunt
INTRODUCTION
This article examines the structure and components of
information storage and retrieval systems and information
filtering systems. Analysis of the tasks performed in such
selection systems leads to the identification of 13
components. Eight are necessarily present in all such
systems, mechanized or not; the others may, but need not
be,
present. The authors argue that all selection systems can
be represented in terms of combinations of these
components. The components are of only two types:
representations of data objects and functions that operate
on them. Further, the functional components, or rules,
reduce to two basic types: 1) transformation, making or
modifying the members of a set of representations, and 2)
sorting or partitioning. The representational
transformations may be in the form of copies, excerpts,
descriptions, abstractions, or mere identifying references.
By partitioning, we mean dividing a set of objects by using
matching, sorting, ranking, selecting, and other logically
equivalent operations. The typical multiplicity of knowledge
sources and of system vocabularies is noted. Some of the
implications for the study, use, and design of information
storage and retrieval systems are discussed.
Information storage and retrieval systems (cata-
logs,
commercial online services, bibliographic utilities,
CD-ROM products) have developed rather empirically
as demand and enabling technology have evolved.
Filtering systems (selective dissemination of information
(SDI) systems,
e-mail
filters) have also developed
pragmatically.
Hitherto, these two types of selection systems were
usually developed and built in relative isolation: a local
retrieval or filtering system designed to work with a
specific data set
in a
particular domain for specific users
and interests, and employing or assuming various kinds
of external knowledge (i.e., thesauri). Perhaps the
practical consideration that such systems have to be
complete in order to work at all has encouraged an
emphasis on the construction and comparison of com-
plete systems rather than on the individual components
(or subsystems) of such systems.
Purpose
Three considerations now encourage detailed
analysis of the components of selection systems:
1) Academic curiosity: Can all information storage
and retrieval systems (or, better, all selection
systems) be viewed as composed of a common
set of components? If so, what are they and how
many are there? Which are necessary and which
are sufficient?
2) Comparative evaluations: The recent Text Re-
trieval Conferences (TREC)1 have provided a
Buckland is professor and Plaunt is a doctoral
student in the School of Library and Information Studies,
University of California, Berkeley.
Acknowledgments: This work was partially support-
ed by the United States Department of Education Higher
Education Act Title IID grant #R197D00017, Prototype
for an Adaptive Library Catalog. We are grateful for the
comments of Clifford A. Lynch and Patrick Wilson.
—
ON THE CONSTRUCTION
OF
SELECTION SYSTEMS
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ISSUE 48
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12:4 (1994) 15
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