The theoretical foundations of recent work on automatic and semiautomatic
thesaurus construction are briefly but critically reviewed, and
limitations of current methods of automatic construction of thesaurus are
pointed out. Need for a deeper study of the theoretical foundations of thesaurus
construction is emphasized and a line of approach to it is suggested

Chose, A.

Dhawle, A.S.

English

Librarians' Digital Library

SEMINAR ON THESAURUS (1975). Paper AB
1
2
INTRODUCTION
THEORETICAL FOUNDATIONS OF THESAURUS CONSTRUCTION
A CHOSE and A S DHAWLE, Vikram Sarabhai Library,
Indian Institute of Management, Vastrapur, Ahmedabad 380 015
The theoretical foundations of recent work on automatic and semi-
automatic thesaurus construction are briefly but critically reviewed, and
limitations of current methods of automatic construction of thesaurus are
pointed out. Need for a deeper study of the theoretical foundations of the-
saurus construction is emphasized and a line of approach to it is suggested.
There are now available thesauri for a
variety of subject-fields ranging from physics,
chemistry and engineering in the physical sci-
ences, through medicine in the biological sci-
ences, to education, political science, and
sociology in the social sciences. It is necessary
to take a close look at the theoretical founda-
tions of thesauri construction in order to eva-
luate the usefulness of thesauri built on that
basis in information retrieval. Thesaurus con-
struction has basically two aspects : (1) Selec-
tion of key words/terms/phrases of the parti-
cular subject for which the thesaurus is con-
structed; and (2) establishing inter-relation-
ship among those terms so as to deal with the
problem of synonimity and display hierarchicalrelationship among terms. The importance of
both these aspects for information retrieval
purposes is evident. In this paper, we show
that whereas the problem of selection of key-
words can be tackled without great difficulty,
and even a fully automatic solution of the prob-
lem is not impracticable, the problem of inter-
relationship of terms presents serious difficul-
ties, particularly for the construction of thesau-
ri of social sciences. We shall discuss these
difficulties fully, and suggest ways to over-
come them.
CURRENT METHODOLOGY
The selection of key words or phrases
for the subject is done by scanning through
documents in a collection, and making one list
of words/phrases significant for information
retrieval purposes and another of common words
(negative dictionary) which are common to most
subjects and hence have no significance for in-
formation retrieval purposes of the subject
under consideration. In preparing the list of
significant words, it is sufficient to consider
only the stems of words so that any other word
derived by the addition of a suffix to the stem
word can be identified with its stem word. This
process would significantly reduce the length
of the list of words.
Fully automatic methods have been suc-
cessfully used for such a selection procedure
(7, 11, 16). This is based an making the com-
puter find out the frequency of terms found in agiven collection of documents, and then choosing
those terms as significant, the frequencies of
which are neither too high nor too low. The
terms of very high frequency are considered as
common words and those of very low frequency
being considered as having little relevance to
the subject. Such terms are considered to be
insignificant from the point of view of informa-
tion retrieval.
Whereas the fully automatic methods
based on frequency of terms seem to be quite
adequate for selection of key words/phrases,
this approach does not appear to us to be a
sound basis for the study of interrelationship of
terms as has been done by some authors (2, 3,
1 0).
	
Let us first consider how this interrela-
tionship of terms is established by means of a
term document matrix. The frequency of
terms in each document belonging to a collec-
tion of document on the subject concerned is
represented in the matrix form as follows
d 1
d 2
d
m
t i
	
t Z
	
t n
f
11
	
f
1z
	
f I n
fml fm2. fmn
A 9
AB2
fi j shows the frequency of the term t j in the
document di (i = 1, 2... m ; j = 1, 2... n).
	
Let
us now consider a simple example
In this example, we find that tl, t 4 are highly
frequent in dl and d2, whereas in d3 and d4,
the frequency of both these terms is low. Simi-
larly for t 2 , t3 we find that they are highly
frequent in d3, d4, and are rare in dl, d2.
Hence, one concludes that tl is related to t4,
and t2 is related to t3.
	
In this way classes of
interrelated terms are formed so that terms
belonging to the same class are characterised
by the fact that they are almost equally frequent
in a set of documents and almost equally rare in
another set of documents.
The frequency approach has also been
used to set up hierarchical relationship among
terms (1). For a class of interrelated terms,
those terms which have substantially higher
frequencies are considered as categories and
those with low frequencies are considered as
sub-categories. Hierarchical relationships
based on frequency of terms might have been
adequate for the information retrieval needs
for a particular subject (1), but there does not
seem to be enough grounds to make it a general
principle for the thesaurus construction for all
subjects. As we had pointed out earlier, set-
ting up hierarchical relationships of terms is
one of the most critical problems of library
classifications (5). It cannot be solved sim-
plistically by counting the frequency of terms.
That a certain amount of human judgement is
essential for setting up interrelationships and
classification of terms is admitted also by
Salton (13). The crucial problem is to deter-
mine how human judgement is to be used for
establishing a classification as well as an inter-
relationship of terms.
Sparck-Jones (14) suggests a way of
determining synonimity of terms by asking the
decision maker whether a term can replace
another term in a given context. If the synoni-
mity of terms established in this way is to be
of use for information retrieval, then the deci-
sion maker's decision should not be too subjec-
tive. Such an element of subjectivity (and con-
A 1 0
CHOSE and DHAWLE
sequently ambiguity for information retrieval
purposes) will inevitably creep in with many of
the terms of social sciences. Consider for
instance, the sentence "A person's behaviour
depends upon his education". If a decision
maker would be asked whether in this sentence
"behaviour" can be replaced by "attitude", his
answer would depend upon the fact whether he
subscribes to behaviouristic psychology or not.
Such examples should caution us about the in-
herent problem of ambiguity of the terms of
social sciences, and hence also about some of
the fundamental difficulties of thesaurus con-
struction.
Question answering system has also been
used to apply human judgement to the problem
of classification of terms and determination of
categories and sub-categories. Actually the
categories and the sub-categories are fixed
first, such as abstract, concrete, etc., and then
questions are asked whether the terms have the
properties expressed by the categories. In
this way one gets a term property matrix.
t i
t 2
t
o
Computer
System
Program
Machine
Equation
Logic
Data
The properties are chosen in such a way that
they are apparently mutually exclusive. For
the term 'computer' there is no ambiguity as
to which of the properties would apply. One
pl
	
pZ
e ll
e
nl
e 12
e
n2
pm
e l m
e
nm
e ij = I means that the property p. is applicable r
to the term ti (i = 1,...n; j = 1_.m). Simi-
larly e ij = 0 implies that pj is not applicable
to ti.
Let us consider a term property matrix
for computer science such as the one consider-
ed by Salton (12).
Abstrac- Physical Hard- Soft-
tion
	
object ware ware
t l
	
t
2
	
t 3
	
t 4
d l 4
	
1
	
0
	
5
d 2 3
	
0
	
1
	
4
d 3 0
	
4
	
6
	
1
d 4 1
	
3
	
4
	
0
would for instance get the corresponding row
for the term 'computer' : 0 1 1 0, that is,
computer is not an abstraction, is a physical
object, is a hardware and not software. For
the terms 'system' and 'program' it is not
quite clear which of the properties apply. For
instance 'program' can be considered as an
abstraction, if it is thought of as a mathema-
tical algorithm, and on the other hand as a
physical object if considered as a 'written thing'.
Similarly 'system' may be both hardware and
software. Sometimes a term may be such that
a Property is neither applicable nor nonapplica-
ble to it. It may be quite meaningless to ask
whether the term 'data' is software or hard-
ware.
Of course if one would be able to choose
such properties which are unambiguously mu-
tually exclusive , then one would also be able
to set up a hierarchical classification of terms
from the term property matrix. For instance
in the previous example one could first get two
mutually exclusive classes of terms, terms
referring to abstract objects, and terms refer-
ring to physical objects. Then within these clas-
ses one would get the mutually exclusive clas-
ses of terms referring to hardware and soft-
ware. However, the assumption of existence of
mutually exclusive classes could be valid in sub-
jects such as mathematics and the natural sci-
ences, where the terms have unambiguous
meaning (4), it is quite untenable in interdisci-
plinary subjects like most of the modern sub-
jects of social sciences (6). It is important to
point out that the term property matrix does not
by itself lead to hierarchical classification of
terms, but a hierarchical classification is al-
ready assumed in the construction of the term
property matrix.
3
	
NEED FOR A NEW APPROACH
Since a thesaurus is constructed for the
information retrieval needs of a class of users,
the interrelationship of terms established in
the thesaurus should correspond to some "word
map", which is common to the vast majority of
this class of users. For subjects such as phy-
sics and engineering such a common "word
map" can be built in consultation with a group
of specialists in the field. If we assume that
such a thesaurus will be used only by people
having substantial knowledge about the subject,
we can safely conclude that the thesaurus will
effectively serve the information retrieval needs
of this class of users. In fact a thesaurus con-
structed on the basis of interrelationship of
terms as viewed by the specialists, provided
Foundations of thesaurus construction
	
AB3
that in general there is sufficient agreement
among them, will have a much stronger founda-
tion than the purely frequency based automatic
classification which can always be falsified by
an error of chance.
We would like to emphasise that a the-
saurus should always be constructed having a
class of users in mind. The construction of
thesaurus of a subject, which will satisfy the
information retrieval needs of all possible users,
appears to us as almost impossible, since this
assumes the existence of a common "word map"
for all users. One tends to think that a thesau-
rus for sociology or political science should not
only be useful for the specialists, but also for
the common man. The dilemma of satisfying
the incompatible needs of the specialists and
the common man is faced by Viet (15). How-
ever, he seems to assume that terms have some
inner logical relationship independent of the re-
lationships as viewed by the specialists. We
do not see any reasons for making this assump-
tion, since this raises many philosophical ques-
tions, such as whether terms have meaning
independent of the people who use these terms.
But in subjects such as political science
and sociology it might even be difficult to find
agreement among the specialists as to the
meaning and interrelationship of terms. How-
ever to what extent there are variations in mea-
ning can be explored by studying the association
of terms used by a group of specialists. An
analysis of the similarity and differences of
such associations can thus be represented as
graph theoretical models of different data struc-
tures. The focus of our problem is different
from that of Quillian (8) but similar design
principles can be employed to set up the "con-
figuration of terms" for the meaning of words,
where there is no intrinsic hierarchy among
the terms, but the term whose meaning is sought
becomes the primary focus, and other terms are
seen only in relation to it. "Most importantly,
in such a model of semantic memory there is
no predetermined hierarchy of superclasses
and subclasses ; every word is the patriarch of
its own separate hierarchy when some search
process starts with it. Similarly, every word
lies at various places down, within the hier-
archies of a great many other word concepts.
Moreover, there are no word concepts as such
that are 'primitive'. Everything is simply de-
fined in terms of some ordered configuration of
other things in the memory" (9). Quillian aims
to simulate human memory by storing words in
the memory of the computer with links corres-
ponding to the association among the words as
is given in a standard dictionary of the English
A 1 1
ABA	 GHOSE and DHAWLE
language. The association of words as given in
a standard dictionary has been taken by him as
a model. For our problem of resolving the
ambiguity of meaning, the standard dictionary
is of no use. For 'ambiguous words", each
individual has his particular system of associa-
tion, and since it is impossible to take into ac-
count all possible individual variations in shades
of meaning, we suggest that researches should
be carried out in order to find out these varia-
tions in as much as they exist among the specia-
lists of a subject. In this way one world be able
to take into account the different shades of mean-
ing inherent in the different point of view of the
users of the thesaurus.
4
	
CONCLUSION
Recent work on thesaurus construction
shows that it is generally assumed that fur a
given subject a hierarchical classification of
terms exists. In the fully automatic approach
one tries to establish such relationships purely
on the basis of frequency of occurrence of
terms in a given collection of documents. In
the semiautomatic approach the experts' ans-
wers to a set of questions give the clues for the
classification. However, in the very framing
of the questions one assumes a priori some
hierarchical classification. In our point of view
a thesaurus should be constructed keeping a
class of users in mind and the interrelationship
of terms can only be established, after an ana-
lysis of their association of terms. This ap-
proach is recommended particularly for the
thesaurus of social sciences where terms tend
to be quite ambiguous.
5
	
BIBLIOGRAPHICAL REFERENCES
I Sec 2 DOYLE (L B). Expanding the
editing function in language
data processing. (Commrn
ACM. 8 ; 1965; )
2
	
Sec 2 --. Is automatic classification a
reasonable application of sta-
tistical analysis of text ?
(J ACM. 12 ; 1965 ; 47A-89)
A
	
Sec Z --. Semantic road maps fur
literature searchers (J ACM
8 ; 1961 ; 551-78)
4
	
Sec 2 GHOSE (A). Logic, Matthew-
A 1 2
in behavioural science - word
concepts : A theory and simu-
lation of some basic semantic
capabilities. (Behav Sci. 12;
1967 ; 410-A0)
9
	
Sec A
	
(--. 415)
10
	
Sec 2 ROLLING (L). EURATOM
thesaurus - Keywords used
within EURATOM's Nuclear
Energy Documentation Project,
Erratum Center for Informa-
tion and Documentation. Rep
E U R. 500.e, 1964.
11
	
Sec 2 SALTON (G). Automatic infor-
mation organization and re-
trieval. 1968. p 40-8
1 2
	
Sec 2 -
	
--- p 51
1A
	
Sec 2 -
	
--. p 57
14 Sec 2 SPARCK-JONES (K). Experi-
ments in semantic classifica-
tion. (Mech Trans. 8; 1965;
97-11 Z)
15 Sec A VIET (J). Thesaurus for infor-
mation processing in sociology.
1971. p 10
16 Sec 2 WALL (E). Vocabulary building
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Duc. 2o; 1969; 161-4).
tics, computer science. (Inter
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5 Sec 2 -- and DHAWLE (A S). Inter-
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knowledge. (Paper presented
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6 Sec 2
7 Sec 2 LESK (M E). Performance of
automatic information systems.
(Infor Stor Retr. 4; 1968;
201-18)
8 Sec A QUILLIAN (M R). Computers


Theoretical foundations of thesaurus construction

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