ONLINE SEARCHING AIDS: A REVIEW OF FRONT ENDS, GATEWAYS AND OTHER INTERFACES
| Published date | 01 March 1990 |
| DOI | https://doi.org/10.1108/eb026861 |
| Pages | 218-262 |
| Date | 01 March 1990 |
| Author | EFTHIMIS N. EFTHIMIADIS |
| Subject Matter | Information & knowledge management,Library & information science |
PROGRESS IN DOCUMENTATION
ONLINE SEARCHING AIDS:
A REVIEW OF FRONT ENDS, GATEWAYS
AND OTHER INTERFACES
EFTHIMIS
N.
EFTHIMIADIS
Centre for Interactive Systems Research
Department of Information
Science,
City
University,
London EC1V 0HB
This review reports on the current state and the potential of tools and systems
designed to aid online searching, referred to here as online searching aids.
Intermediary mechanisms are examined in terms of the two stage model, i.e.
end-user, intermediary, 'raw database', and different forms of user – system
interaction are discussed. The evolution of the terminology of online searching
aids is presented with special emphasis on the expert/non-expert division.
Terms defined include gateways, front-end systems, intermediary systems and
post-processing. The alternative configurations that such
systems
can have and
the approaches to
the
design of
the
user interface are discussed.
The
review then
analyses the functions of online searching aids, i.e. logon procedures, access to
hosts,
help features, search formulation, query reformulation, database
selection, uploading, downloading and post-processing. Costs are then briefly
examined. The review concludes by looking at future trends following recent
developments in computer science and elsewhere. Distributed expert based
information systems (DEBIS), the standard generalised mark-up language
(SGML),
the client-server model, object-orientation and parallel processing are
expected to influence, if they have not done so already, the design and
implementation of future online searching aids.
1.
OVERVIEW
THE PURPOSE OF THIS REVIEW is to indicate the current state and the
potential of tools and systems designed to aid online searching, referred to
here as online searching aids. It is not intended to be exhaustive, either of
the literature or of the systems. Therefore, selected recent and current work
in information retrieval (IR) is reviewed. A number of systems have
been used for illustrating the discussion. A large number of systems also
exist that have not been referred to in this
review.
The review also covers areas
other than information retrieval in a selective manner. Finally, some
suggestions are made concerning future areas of development of searching
aids.
This review is the second part of a British Library funded project at the City
University; the
first
part resulted in the publication of a bibliography on online
searching
aids[1].
Journal
of
Documentation,
Vol.
46, No. 3, September 1990, pp. 218–262.
218
September 1990 ONLINE SEARCHING
2.
INTRODUCTION
Online searchers, in their quest for information, are faced with a wealth of
resources and a wide variety of service centres for accessing the databases.
They must also confront a bewildering number of access protocols, system
designations on different telecommunication networks,
passwords,
command
languages, file loading techniques, system features, system responses and
system messages, data element designators, print formats, terminal speci-
fications, and shortcuts for commands, e.g. functions keys[2].
Having passed this stage successfully the user
is
then faced with
the
inherent
problem in traditional IR, i.e. term matching. Whatever the retrieval
mechanism and the retrieval technique used by the system (see Belkin and
Croft[3]) terms from
the
user's query
are
matched at a
symbolic,
text
matching
level against document representations. This form of matching is some
distance removed from any semantic and contextual information in the
document. Effective use of existing Boolean
IR
systems depends heavily on the
user's perception of the data structure that their queries are addressing. The
data structure (database view) is reflected in the query language, and vice
versa. In other
words,
present query languages reflect the model of the logical
structure of the databases. The IR situation is confined to set operations
(creation and manipulation). Successful handling of these operations results
in a final set which to some degree satisfies the user's expressed information
need.
Online retrieval of whatever sort allows the searcher to make a stab at a
search, and then try again if the results are not satisfactory. Nobody wants to
go back to the situation of batch searching, where the user had only one
attempt in a reasonable timescale. This paradigm is made explicit and
extensively analysed in Belkin and Vickery[4].
2.1
Intermediary mechanisms
The interaction in IR is complicated by the existence of various kinds of
intermediary mechanism. Many IR situations can be conceptualised in
something like the form indicated in Figure 1. A simple two stage model
describing it includes the end-user, the intermediary mechanism, and the raw
database[5].
This intermediary mechanism may be a human being or some
software, for e.g. a user interface, front-end system or expert system. There
may also be more than one intermediate stage.
If
we
consider the interaction possibilities in the above diagram, the picture
becomes
very
complex.
There
may
be
interaction between
the
end-user and the
219
JOURNAL OF DOCUMENTATION Vol. 46, no. 3
intermediary, without reference to the database; interaction between the
intermediary and the database without reference to the end-user; or
interaction that spans
all
three
parties.
In
this
last
case,
messages from the end-
user may or may not be interpreted by the intermediary before being
transmitted to the database; and similarly with return messages. Inter-
pretation may mean anything from a slight rearrangement to a complete
change of form, syntactically and/or semantically.
Much recent research is informed by the perception that some (human or
machine) intermediary is desirable, specifically to encourage interaction and
feedback. It
is
usually suggested that this desirability is simply the result of the
inadequacy of the raw database, though the conceptualisation of IR as
involving an intermediary mechanism seems to represent some deeper
recognition of
the
centrality of feedback.
If we take a narrow view of what constitutes the IR system in a given IR
situation, it would probably be seen as the raw database in the terminology of
Figure
1.
But a general systems theory approach would suggest taking at least
the whole of Figure
1
as the system to be examined. In that view, the user
would not be seen as an independent entity, but as part of
the
system.
But looking at the situation from the user's point of
view,
it must be clear
that the user sees the IR system as something outside
himself,
which he
approaches and from which he expects something. In this view, the system
must be everything in Figure
1
except the user (but including the interaction
between the intermediary and the user).
For the
IR
theorist, it may be that some compromise between these last two
views would be appropriate. If we take into consideration the model of
communication described in the Belkin/Vickery review[4], in which each
participant has a model of the other, then we may perhaps take the user's
model of
the
system to be itself part of
the
system. Thus the boundary of the
system (that is, the system of concern to the
IR
theorist or designer) would
occur somewhere within the mind of the user.
2.2
User-system interaction
We now
consider the interactions which may take place between a human user
and a machine system. In terms of the two-stage model any mechanical
intermediary
is
part of the machine
system.
However, a similar analysis would
apply to the interaction between a human intermediary and a raw database.
In this interaction several levels of complexity might be identified.
Examining first the information going from the system to the user, systems
may provide information about their own facilities, for example error
messages, command menus and help screens. Secondly, they may provide
subject-related information, such as menus of subjects or thesaurus or
dictionary extracts and finally information deriving from an actual search.
This last category includes partial or full records, and statistical information
such as numbers of postings. Some types of information may come into more
than one
category:
e.g.
an analysis of term occurrences
in
a retrieved set comes
into the second and third groups.
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