Ming Lian's research while affiliated with Tianjin University of Technology and other places

Publication (1)

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The hybrid neural network model proposed in this paper consists of two main parts: extracting local features of text vectors by convolutional neural network, extracting global features related to text context by BiLSTM, and fusing the features extracted by the two complementary models. In this paper, the pre-processed sentences are put into the hyb...


... To the best of our knowledge, our framework is the first study to incorporate all important factors into a unified model, including user surface features, temporal information, explicit and implicit social influence, group-aware retweeting factor and user/author's content information. Although the combination of CNN and BLSTM has been proposed in emotional analysis [12], we design them as a sequential structure in A_F_BLSTM_CNN model and add an extra attention mechanism to generate attention probabilities for different tweets in user/author's history. Besides, the FEBDNN framework also includes a novel joint embedding module DAE, which is an extension of traditional auto-encoder network with two inputs, two outputs and a common hidden layer. ...