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The point of it (1)…
The idea here is to refine associates by grouping together words which are found as key in the same sub-sets of text files. The example used to explain associates will help.
Suppose the word wine is a key key-word in a set of texts, such as the weekend sections of newspaper articles. Some of these articles discuss different wines and their flavours, others concern cooking and refer to using wine in stews or sauces, others discuss the prices of wine in a context of agriculture and diseases affecting vineyards. In this case, the associates of wine would be items like Chardonnay, Chile, sauce, fruit, infected, soil, etc. The associates procedure shows all such items unsorted.
The clumping procedure, on the other hand, attempts to sort them out according to these different uses. The reasoning is that the key words of each text file give a condensed picture of its "aboutness", and that "aboutnesses" of different texts can be grouped by matching the key word lists. Thus sets of key words can be clumped together according to the degree of overlap in the key word lexis of each text file.
The initial clumping process does no grouping: you will simply see each set of key-words for each text file separately. To group clumps, you may simply join those you think belong together (by dragging), or regroup with help by pressing .
The listing shows clumps sorted in alphabetical order. You can re-sort by frequency (the number of times each key word in the clump appeared in all the files which comprise the clump).