title: Document Analysis and Tagging
body: <p>Let's say I have a bunch of essays (thousands) that I want to tag, categorize, etc.  Ideally, I'd like to train <em>something</em> by manually categorizing/tagging a few hundred, and then let the thing loose.</p>
  
  <p>What resources (books, blogs, languages) would you recommend for undertaking such a task?  Part of me thinks this would be a good fit for a <a href="http://www.process.com/precisemail/bayesian_filtering.htm" rel="nofollow">Bayesian Classifier</a> or even <a href="http://en.wikipedia.org/wiki/Latent_semantic_analysis" rel="nofollow">Latent Semantic Analysis</a>, but I'm not really familiar with either other than what I've found from a few <a href="http://rubyforge.org/projects/bishop/" rel="nofollow">ruby</a> <a href="http://classifier.rubyforge.org/" rel="nofollow">gems</a>.</p>
  
  <p>Can something like this be solved by a bayesian classifier?  Should I be looking more at semantic analysis/natural language processing?  Or, should I just be looking for keyword density and mapping from there?</p>
  
  <p>Any suggestions are appreciated (I don't mind picking up a few books, if that's what's needed)!</p>