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Neural network models have been demonstrated to be capable of achieving remarkable performance in sentence and document mod-eling. Convolutional neural network (CNN) and recurrent neural network (RNN) are two mainstream architectures for such modeling tasks, which adopt totally different ways of understanding natural languages. In this work, we combine the(More)
Distributed word representations have been demonstrated to be effective in capturing semantic and syntactic regularities. Unsuper-vised representation learning from large un-labeled corpora can learn similar representations for those words that present similar co-occurrence statistics. Besides local occurrence statistics, global topical information is also(More)
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