Sparck Jones has carried on this work using measures of association between keywords based on their frequency of co-occurrence (that is, the frequency with which any two keywords occur together in the same document).
She has shown that such related words can be used effectively to improve recall, that is, to increase the proportion of the relevant documents which are retrieved.
Interestingly, the early ideas of Luhn are still being developed and many automatic methods of characterisation are based on his early work.
The term information structure (for want of better words) covers specifically a logical organisation of information, such as document representatives, for the purpose of information retrieval.
The development in information structures has been fairly recent.
The main reason for the slowness of development in this area of information retrieval is that for a long time no one realised that computers would not give an acceptable retrieval time with a large document set unless some logical structure was imposed on it.
In fact, owners of large data-bases are still loath to try out new organisation techniques promising faster and better retrieval.
The slowness to recognise and adopt new techniques is mainly due to the scantiness of the experimental evidence backing them.
The earlier experiments with document retrieval systems usually adopted a serial file organisation which, although it was efficient when a sufficiently large number of queries was processed simultaneously in a batch mode, proved inadequate if each query required a short real time response.
The popular organisation to be adopted instead was the inverted file.
By some this has been found to be restrictive (Salton).
More recently experiments have attempted to demonstrate the superiority of clustered files for on-line retrieval.
The organisation of these files is produced by an automatic classification method.
Good and Fairthorne were among the first to suggest that automatic classification might prove useful in document retrieval.
Not until several years later were serious experiments carried out in document clustering (Doyle; Rocchio).
All experiments so far have been on a small scale.
Since clustering only comes into its own when the scale is increased it is hoped that this book may encourage some large scale experiments by bringing together many of the necessary tools.
Evaluation of retrieval systems has proved extremely difficult.
Senko in an excellent survey paper states: 'Without a doubt system evaluation is the most troublesome area in ISR ...', and I am inclined to agree.
Despite excellent pioneering work done by Cleverdon et al. in this area, and despite numerous measures of effectiveness that have been proposed (see Robertson[22, 23 ]for a substantial list), a general theory of evaluation had not emerged.
I attempt to provide foundations for such a theory in Chapter 7 (page 168).