This paper fills these gaps and significantly extends the work of (Rutherford and Xue, 2014) by explicitly comparing various types of word representations and vector composition methods.
we investigate three well-known word embeddings, namely Collobert and Weston (Collobert and Weston, 2008), hierarchical log-bilinear model (Mnih and Hinton, 2007) and Hellinger Principal Component Analysis (Lebret and Collobert, 2014), in addition to Brown clusterbased and standard one-hot representations.