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Unsupervised joke generation from big data

acl2013.org

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Re: Unsupervised joke generation from big data

#2
Edit: The actual paper: http://homepages.inf.ed.ac.uk/s0894589/petrovic13unsupervise... (thanks to jaryd - I was certain the page on acl2013.org linked to it last time I checked...)

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I like my papers like I like my women - in LaTeX.

(I realise that doesn't fit the rules set down in the paper... or those here on HN to survive title-moderation ;-) )

More from the Register: http://www.theregister.co.uk/2013/08/02/heard_the_one_about/

And here's how the Scotsman covered it (around the start of the Edinburgh festival): http://www.scotsman.com/the-scotsman-2-7475/scotland/scienti...

Re: Unsupervised joke generation from big data

#7
post #6

"I like my relationships like I like my source, open I like my coffee like I like my war, cold I like my boys like I like my sectors, bad" These are the funny jokes. Enthusiasm tempered.

To be fair, these jokes do clearly follow the 4 points laid out in the article.

In addition, I did snicker at #2.

Re: Unsupervised joke generation from big data

#9
post #6

"I like my relationships like I like my source, open I like my coffee like I like my war, cold I like my boys like I like my sectors, bad" These are the funny jokes. Enthusiasm tempered.

Their joke model misses one thing: each noun has to be commonly used in the phrase "I like my ". People often say "I like my coffee black" but nobody ever says "I like my source open." I think that is why they sound weird. But I like the off-kilter unexptectedness.
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