IIA U T O M A T I C

II • 1I N D E X I N GP R O C E D U R E S

Semantics and syntax

I shall consider automatic indexing under the four heads
listed in Section I, namely analysis, description, index language
generation, and searching, while recognising that operations
fulfilling the same logical function may be carried out at different
points in particular systems.
It is convenient to separate semantics and syntax, since inmany systems they are clearly or effectively distinguished, even if
ultimately there is little justification for labelling someconceptual category or relation syntactic or semantic.

The semantics of a retrieval system cover1

from the document or request processing point of viewa)b)c)2

in analysis, the identification of words or simple concepts
in description, the provision of index terms or descriptors
in searching, the exploitation of paradigmatic or classrelations between terms;

from the index language point of viewa)b)in generating the vocabulary, the choice of terms or descriptors
in organising the vocabulary, the establishment of paradigmatic
relations between terms.

The syntax of a retrieval system concerns
1

from the document point of viewa)b)c)

2

in analysis, the identification of syntactic roles and relations
in description, the provision of relational informationin searching, the exploitation of syntagmatic relations between
terms;

from the language point of viewa)b)in generating indicators, the choice of syntagmatic or logicalrelators to connect terms or descriptors
in organising indicators, the establishment of modulation rules
permitting changes to forms of syntactic structure.

As noted, the operations under most of these headings may be
carried out partly or wholly automatically, and hence are covered by
the label automatic indexing.

2.1

For example9 for semantics, underlabc

2abwords may be extracted automatically using frequency criteria
terms from a thesaurus may be assigned via the text density ofentry words
keywords may be connected through their statistical classrelations?
descriptors may be provided by keyword grouping
formal hierarchial relations may be established between termclasseSoFor syntax,, underlabc

nominal or verbal word groups may be identified by parsing
logical relations may be associated with specific text syntax
structuressyntagmatic relations between terms may generalised;.}automation dubious.

HoldDocuments and requests

In many cases9 indexing procedures applied to documents may also
be applied to requests (or profiles) 0 For example, if a controlledindexing language is used, both documents and requests must be translated
into ito In other cases, the direct treatment of documents and requests
is not the sameQ For example, if documents are represented by simple
lists of keywords, a Boolean request explicitly defines term relationships
which are only implicit in the document descriptions. Another example isthe use of truncated words in the search specification where thedocuments are indexed by full words0 Although in a given search theeffect is the same as if a matching document is indexed by truncatedwords, greater flexibility of indexing in relation to different searches
is implieds truncating request words only allows alternative specifications
with varying selective power0 For example, if we search on 'comput-' weretrieve documents indexed by 'computer9, "computers', 'computing' and0computation\ but if we search on "computer-0 we retrieve the first two
onlyQ
We must therefore allow documents and requests to differ both insyntactic structure and in indexing vocabulary, though clearly differencesof treatment cannot be carried too far. However, as most forms ofdescription may be used for either documents or requests, references
to document description should be generally interpreted to cover request
description as well 0 Some analysis procedures, specifically statisticalones, are obviously not appropriate to requests, but these cases should
be obviouso Specific remarks about requests will be included in thediscussions of searching02o2

II . 2

Secondary system factors

There are many system factors affecting performance in general,and hence automatic indexing performance, but only indirectly? they
are outside the actual indexing procedure. These factors may be
assigned to two categories, less and more immediate.

II.2.1Less immediate factors

These include gross system properties and constraints which may
not be open to modification in the interests of indexing performance.
For example,
1 re the collection:
its size (particularly in operational systems), subject matter,
type of document, language etc., which may present particular
problems if, for example, different types of document areincluded, or material in several languages;
2 re the mode of operation:
provision for different types of user and service from thesame basic document material;
3 re the cost of the operation:requirements to restrict costs, typically by adherence to simple
techniques,II.2.2More immediate factors

These include factors affecting individual documents and requests.

Choice of input text
It is generally assumed that the choice of input text offeredto the system for indexing affects performance. There are threeobvious possibilities, full document text, abstract, and title. A
number of comparisons to determine the relative value of these formanual indexing have been carried out, for example by Cleverdon 1966,
Saracevic 1968, 1971 and Aitchison 1970. In general the results
reported agree in finding titles as a base for indexing deficient inrecall compared with abstracts or full text, though precision is good.
Saracevic found a progressive increase in recall and decline inprecision moving from titles to abstracts to text. Some comparisonswith automatic indexing of a straightforward kind have also been carriedout: Cleverdon and Aitchison compared titles and abstracts, and Salton
1968a titles, abstracts and full (short) text. The first two foundtitles inferior to abstracts on recall but superior on precision.
Salton*s rather different matching function showed an overall
improvement in performance from titles to text; he claims there is lessdifference between abstract and text than between title and abstract.

2.3

Unfortunately different sources tend to be associated with different
levels of indexing exhaustivity, so the comparisons are not confined
to a single system factor0 From an economic point of view it is ofinterest that though titles tend to perform indifferently, their defects
may not be striking, and they are very cheap* If abstracts are machine
held for independent reasons, for example for circulation in an SDIsystem^? they may as well be usedo It is not obvious how much is reallygained from working with full text.

Degree of request vetting
The amount of work that is put into checking a request's intention
before it is offered to the system may make a difference to the system's
performanceo
In particular we can expect iterative searching withfeedback to influence performance substantially. This is consideredlateroRelevance
How much different interpretations of relevance affect system
performance is not clear0 Many experiments have allowed for different
degrees of relevance,, and control tests have been carried out withdifferent relevance sets to check comparative indexing performance,
Cn the whole we must expect grossly different relevance needs to suggest
different approaches to indexing <,Matching functions
The matching function used during searching is logically independentof the form of indexing used? but its influence on performance may beconsiderableo Most retrieval systems use simple matching functions
associated with Boolean request specifications, with the requirement thatthe full specification must be satisfied for a document to be retrieved.
If terms are simply coordinated, and matches on decreasing subsets areallowed, we have the familiar coordination level approach* If terms areweighted, within this framework, we have notional coordination levels.
However some workers have advocated more sophisticated matching functions
leading to a more discriminating ranking of output, through normalisation totake account of varying document and request description length. Thisapproach is adopted by the Smart project, and van Rijsbergen 1971, 1972,
Salton 1968apc argued that such functions improve performance, comparing
performance for the overlap and cosine correlation functions forthree collectionss the cosine function performed noticeably better for
two and no worse for the thirdo In some environments, where descriptions
do not vary much, such functions would not be expected to perform better.

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