pork = pig + meat
So the year of 2015 is the year of ram/sheep/goat, in Chinese they literally means
Ram = male ∪ caprinae
sheep = wool ∪ caprinae
goat = mountain ∪ caprinae
basically, word composition is pretty common in analytic language like Chinese, but kinda new idea in fusional languages like English.
Learning a language that is based on different principles is an enormous brain exercise. Also, remembering the characters is a challenge.
Here is the demo webpage for the sentiment analysis system: http://nlp.stanford.edu/sentiment/
This link is about document distances but still compares other techniques nicely:
However, why are there words more similar to "vacation" than "vacation"?
If it's the first option, then generating those descriptions seems and important thing to mention.
If it's the second, then it's a pretty significant result! I've seen some papers that indicate some possibilities in that area, but never anything working as well as this.
So we don't do any fancy deep learning from the images themselves, although this is on the horizon :)
(Speaking as one of the authors of the post)
Reminds me of my java textbook: the example was to model some employee and it's gender was a `boolean`: `false` for man; `true` for woman. Of course that was just an intermediate example before they showed off the `enum` solution.
 because hey, java OOP + CRUD business application example == match made in heaven as an example, apparently.