8. The method of claim 7 , wherein determining the author vector for the first author using the trained neural network system comprises performing a respective iteration of gradient descent for each of the plurality of first sequences of words to adjust the author vector for the first author from a previous iteration of gradient descent.
8. The method of claim 7 , wherein determining the author vector for the first author using the trained neural network system comprises performing a respective iteration of gradient descent for each of the plurality of first sequences of words to adjust the author vector for the first author from a previous iteration of gradient descent. 9. The method of claim 8 , wherein the performing the respective iteration of gradient descent for each of the plurality of first sequences of words comprises: mapping each of the words in the first sequence to a vector representation using the embedding layer; combining the vector representation for the words in the first sequence with the author vector for the first author from the previous iteration to generate a combined representation; generating word scores from the combined representation; computing a gradient using the word scores and the word that follows the first sequence from the set of words; and adjusting the author vector for the first author from the previous iteration using the gradient.