K-means document clustering - what next? [closed]

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I am trying to learn some hands-on techniques in datamining and machine learning. I just implemented a k-means clustering algorithm, and as far as I can tell it works fine. I understand that it finds patterns in the data where no structure was previously known, but my question is, what can I do with this information now? I want to take my code to the next step, so I am curious - once I have k clusters of a bunch of documents, how does that help me understand the data? What can I do with this newfound information? More specifically, I am looking for a coding project that will take my clustering implementation to the next level.

Answer 1

k-means and other clustering algorithm group items and provide usefull information about your documents' set, then clustering can be used to

1. find related document
2. have a short overview of your set

when you use different metric and different cluster you can provide to user tags view or graph like that

http://blog.cluster-text.com/tag/cluster/