<story><title>A Word Is Worth a Thousand Vectors</title><url>http://technology.stitchfix.com/blog/2015/03/11/word-is-worth-a-thousand-vectors/</url></story><parent_chain></parent_chain><comment><author>est</author><text>As a native Chinese speaker, this comes so natural.&lt;p&gt;pork = pig + meat&lt;p&gt;So the year of 2015 is the year of ram&amp;#x2F;sheep&amp;#x2F;goat, in Chinese they literally means&lt;p&gt;Ram = male ∪  caprinae&lt;p&gt;sheep = wool ∪ caprinae&lt;p&gt;goat = mountain ∪ caprinae&lt;p&gt;basically, word composition is pretty common in analytic language like Chinese, but kinda new idea in fusional languages like English.</text></comment>
<story><title>A Word Is Worth a Thousand Vectors</title><url>http://technology.stitchfix.com/blog/2015/03/11/word-is-worth-a-thousand-vectors/</url></story><parent_chain></parent_chain><comment><author>madcowherd</author><text>Wondering how this differs from the SemanticVectors package?  Will have to look into word2vec further.</text></comment>