The Text Mining Process

Whether you intend to use textual data for descriptive purposes, predictive purposes, or both, the same processing steps take place, as shown in the following table:
File preprocessing
Creates a single SAS data set from your document collection. The SAS data set is used as input for the Text Miner node and might contain the actual text or paths to the actual text.
%TMFILTER macro — a SAS macro for extracting text from documents and creating a predefined SAS data set with a text variable
Text parsing
Decomposes textual data and generates a quantitative representation suitable for data mining purposes.
Text Miner node
Transformation (dimension reduction)
Transforms the quantitative representation into a compact and informative format.
Text Miner node
Document analysis
Performs clustering, classification, prediction, or concept linking of the document collection.
Text Miner node or SAS Enterprise Miner predictive modeling nodes
Finally, the rules for clustering or predictions can be used to score a new collection of documents at any time.
You might not need to include all of these steps in your analysis, and it might be necessary to try a different combination of text-parsing options before you are satisfied with the results.