I'm not quite sure what to think of that, but at least it was reasonably consistent for me.
I suspect the webapp is just suggesting random writers.
Also, NLP classification is a hard problem. I don't think doing it reliably over a weekend is possible. I think that had OP done any good work on NLP, he would have discussed it. I am more inclined to think the app is just giving random results.
I gave it a slice of Finnegan's Wake, and it told me it sounded like James Joyce. It would be a pretty bad algorithm if it couldn't identify James Joyce.
Then I got it to correctly identify passages from Dan Brown and Mario Puzo. Quite impressive.
One possibility is that it's just matching word frequencies. To check this, I tried a few strings of my own devising:
"mafia mafia don don mafia mafia" --> Mario Puzo
"vatican conspiracy vatican conspiracy vatican conspiracy" --> Dan Brown
"oh woe is me, life sucks, everything is crap" --> Chuck Palahniuk
Nope. It's just a Bayesian classificator :)
You might also connect with the people who try to identify students who turn in term papers and lab reports written by other people.
You could also add a game (who wrote the following paragraph? (Multiple choice)). That would be an avenue for return visitors.
You could also have "write like Hemingway / Dickens / Neal Stephenson / etc." contests. Kinda like painters going to famous museums and copying the works of famous painters, it's a way to extend and hone the craft of writing. I recall a good version of Twas The Night Before Christmas written as if Hemingway wrote it. Also, connect with specific writers' fanbases (especially Chuck Palahniuk), and with writers workshops, and fanfic groups. Poetry, too.
There are a lot of ways you could take this. Make sure your algorithm is effective, though!
You suggestions are helpful. Now that I'm interested in this topic, I may release something better. Thanks.