Generating document representatives - conflation
Ultimately one would like to develop a text processing system which by means of computable methods with the minimum of human intervention will generate from the input text (full text, abstract, or title) a document representative adequate for use in an automatic retrieval system.
This is a tall order and can only be partially met.
The document representative I am aiming for is one consisting simply of a list of class names, each name representing a class of words occurring in the total input text.
A document will be indexed by a name if one of its significant words occurs as a member of that class.
Such a system will usually consist of three parts: (1) removal of high frequency words, (2) suffix stripping, (3) detecting equivalent stems.
The removal of high frequency words, 'stop' words or 'fluff' words is one way of implementing Luhn's upper cut-off.
This is normally done by comparing the input text with a 'stop list' of words which are to be removed.
Table 2.1 gives a portion of such a list, and demonstrates the kind of words that are involved.
The advantages of the process are not only that non-significant words are removed and will therefore not interfere during retrieval, but also that the size of the total document file can be reduced by between 30 and 50 per cent.
The second stage, suffix stripping, is more complicated.
A standard approach is to have a complete list of suffixes and to remove the longest possible one.
Table 2.2 lists some suffixes.
Unfortunately, context free removal leads to a significant error rate.
For example, we may well want UAL removed from FACTUAL but not from EQUAL.
To avoid erroneously removing suffixes, context rules are devised so that a suffix will be removed only if the context is right.
'Right' may mean a number of things:
(1) the length of remaining stem exceeds a given number; the default is usually 2;
(2) the stem-ending satisfies a certain condition, e.g. does not end with Q.
Many words, which are equivalent in the above sense, map to one morphological form by removing their suffixes.
Others, unluckily, though they are equivalent, do not.
It is this latter category which requires special treatment.
Probably the simplest method of dealing with it is to construct a list of equivalent stem-endings.
For two stems to be equivalent they must match except for their endings, which themselves must appear in the list as equivalent.
For example, stems such as ABSORB- and ABSORPT- are conflated because there is an