"Mining standard text and then creating clusters?"

Hi there,

I am relatively new to Rapid Miner, and data mining too for that matter.

I have just installed Rapid Miner and have been through the tutorial and studied the various literature.

I wanted to know if it was possible for Rapid Miner to be fed with paragraphs of standard written english text (in a *.dat file), and then for it to parse through all the paragraphs and to identify patterns within the text (i.e. could be certain keywords or phrases that appear to be similar). Then Rapid Miner should decide that there should be x clusters as a result of the parsed text, and it puts (or assigns) each paragraph within the *.dat file to a cluster.

I have heard this it is possible to do this using some form of unsupervised learning model?

Any ideas from the community on how this could be tackled?

I also was having difficult importing text into Rapid Miner using the ExampleSource IO operator, so any guidance here would be highly appreciated too.

Thanks for your time.

Ritesh