More specifically, in pre-coordinate indexing a logical combination of any index terms may be used as a label to identify a class of documents, whereas in post-coordinate indexing the same class would be identified at search time by combining the classes of documents labelled with the individual index terms.
One last distinction, the vocabulary of an index language may be controlled or uncontrolled.
The former refers to a list of approved index terms that an indexer may use, such as for example used by MEDLARS.
The controls on the language may also include hierarchic relationships between the index terms.
Or, one may insist that certain terms can only be used as adjectives (or qualifiers).
There is really no limit to the kind of syntactic controls one may put on a language.
The index language which comes out of the conflation algorithm in the previous section may be described as uncontrolled, post-coordinate and derived.
The vocabulary of index terms at any stage in the evolution of the document collection is just the set of all conflation class names.
There is much controversy about the kind of index language which is best for document retrieval.
The recommendations range from the complicated relational languages of Farradane et al. and the Syntol group (see Coates for a description) to the simple index terms extracted by text processing systems just described.
The main debate is really about whether automatic indexing is as good as or better than manual indexing.
Each can be done to various levels of complexity.
However, there seems to be mounting evidence that in both cases, manual and automatic indexing, adding complexity in the form of controls more elaborate than index term weighting do not pay dividends.
This has been demonstrated by the results obtained by Cleverdon et al., Aitchison et al., Comparative Systems Laboratory and more recently Keen and Digger .
The message is that uncontrolled vocabularies based on natural language achieve retrieval effectiveness comparable to vocabularies with elaborate controls.
This is extremely encouraging, since the simple index language is the easiest to automate.
Probably the most substantial evidence for automatic indexing has come out of the SMART Project (1966).
Salton recently summarised its conclusions: ' ... on the average the simplest indexing procedures which identify a given document or query by a set of terms, weighted or unweighted, obtained from document or query text are also the most effective'.
Its recommendations are clear, automatic text analysis should use weighted terms derived from document excerpts whose length is at least that of a document abstract.
The document representatives used by the SMART project are more sophisticated than just the lists of stems extracted by conflation.