As a native Chinese speaker, this comes so natural.<p>pork = pig + meat<p>So the year of 2015 is the year of ram/sheep/goat, in Chinese they literally means<p>Ram = male ∪ caprinae<p>sheep = wool ∪ caprinae<p>goat = mountain ∪ caprinae<p>basically, word composition is pretty common in analytic language like Chinese, but kinda new idea in fusional languages like English.
I've always wondered about doing this in non-flat spaces. Like if I add the "7100 miles west" vector to the "California" point, I get Turkmenistan. If I add "7100 miles west" again, I get back near "California." Similarly, adding the "not" vector twice might get you back where you started in a word embedding. Anyone know if anyone is working on this? It could be tricky because "7100 miles west" lives in the tangent space to the space "California" lives in, but that in itself could be an interesting thing to study in the context of words.
Very exciting stuff. I love how you can take simple building blocks and create something elegant and fun with them.<p>However, why are there words more similar to "vacation" than "vacation"?
I don't understand how the item matching is working. Do they have textual descriptions of each item (including colors and patterns), or are they somehow building vectors for the images and then doing cross-modal vector calculations?<p>If it's the first option, then generating those descriptions seems and important thing to mention.<p>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.
> If the gender axis is more positive, then it's more feminine; more negative, more masculine.<p>Reminds me of my java textbook: the example was to model some employee[1] 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.<p>[1] because hey, java OOP + CRUD business application example == match made in heaven as an example, apparently.