citromatik,
You really didn't answer my last question which means I probably didn't ask it well. Is your goal only to identify duplicate articles (typos and what not) or is it to group related articles as well? If it is to group related articles, what criterion are you using. I gave an example relating to social network sites. A "loose" group might be anything having to do with a social networking site where a "tighter" group might only have to do with lawsuits against Facebook.

What do you intend to do if an article can belong to more than one cluster? You mentioned that it would be considered a bug if an article ended up in the wrong cluster - how would you know? Is there a subjective element to this task or can you define the criterion for clustering in black and white terms. In other words, if randomly selected 1000 articles and were to cluster them by hand - could you write code that would produce the same results (where computational time is not a factor)?

Cheers - L~R

In reply to Re^3: Cluster a big bunch of strings by Limbic~Region
in thread Cluster a big bunch of strings by citromatik

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