Recently deeplearning models have been shown to be capable of making
remarkable performance in sentences and documents classification tasks. In this
work, we propose a novel framework called AC-BLSTM for modeling sentences and
documents, which combines the asymmetric convolution neural network (ACNN) with
the Bidirectional Long Short-Term Memory network (BLSTM)...
demonstrate that our model achieves state-of-the-art results on five tasks,
including sentiment analysis, question type classification, and subjectivity
classification. In order to further improve the performance of AC-BLSTM, we
propose a semi-supervised learning framework called G-AC-BLSTM for text
classification by combining the generative model with AC-BLSTM.