Abstractive Sentence Summarization with Attentive Recurrent Neural Networks
- 摘要
Abstractive Sentence Summarization generates a shorter version of a given sentence while attempting to preserve its meaning.
We introduce a conditional recurrent neural network (RNN) which generates a summary of an input sentence. （我们将介绍一种条件递归神经网络，其用来生成输入句子的摘要）
The conditioning is provided by a novel convolutional attention-based encoder which ensures that the decoder focuses on the appropriate input words at each step of generation. （使用一种conditional RNN来生成摘要，该条件是卷积注意力模型（convolutional attention-based encoder），用来确保每一步生成词的时候都可以聚焦到合适的输入上。）
Our model relies only on learned features and is easy to train in an end-to-end fashion on large data sets. （模型仅仅依赖于学习到的features，并且很容易在大规模数据上进行end2end式训练）
Our experiments show that the model significantly outperforms the recently proposed state-of-the-art method on the Gigaword corpus while performing competitively on the DUC-2004 shared task.（在Gigaword语料上和DUC-2004任务中取得了更好的效果。）