"The Hatter opened his eyes very wide on hearing this; but all he SAID was, 'Why is a raven like a writing-desk?' 'Come, we shall have some fun now!' thought Alice. 'I'm glad they've begun asking riddles. - I believe I can guess that,' she added aloud. 'Do you mean that you think you can find out the answer to it?' said the March Hare."
– Lewis Carroll, Alice in a Wonderland
Why is a raven like a writing desk? With the help of distributive semantic and vector word representations, finally we can help Alice to solve Hatter's riddle (in a mathematically precise way):
In [42]: model.most_similar('house', topn=5) Out[42]: [(u'camp', 0.8188982009887695), (u'cabin', 0.8176383972167969), (u'town', 0.7998955845832825), (u'room', 0.7963996529579163), (u'street', 0.7951667308807373)] In [43]: model.most_similar('America', topn=5) Out[43]: [(u'India', 0.8678370714187622), (u'Europe', 0.8501001596450806), (u'number', 0.8464810848236084), (u'member', 0.8352445363998413...