Other models such as skipthought vectors (Kiros et al., 2015) and SDAE<cite> (Hill et al., 2016)</cite> requires building an encoder-decoder model which takes time 3 to learn. For other models like paragraph vectors (Le and Mikolov, 2014) and Fastsent vectors<cite> (Hill et al., 2016)</cite> , they require a gradient descent inference step to compute the paragraph/sentence vectors. Using the DoCoV, we just require a pre-trained word embedding model and we do not need any additional training like encoder-decoder models or inference steps via gradient descent.