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NLP Summarization: Abstractive Neural Headline Generation Over A News Articles Corpus

机译:NLP摘要:Abstactive神经标题一代通过新闻文章语料库

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Most of NLP research fields (Translation, Classification, Dialogue Systems …) have been revolutionized by the rise of deep learning methods, which rely on the new dense and low-dimensional feature representation. We present in this article the basic training techniques of Word Embeddings as well as the recent works on Abstractive Neural Summarizers. We also introduce our trained French Word Embeddings, further used as the embedding layer to implement our baseline French Neural Summarizer for the headline generation task, using the RNN (Recurrent Neural Network) Encoder-Decoder architecture.
机译:大多数NLP研究领域(翻译,分类,对话系统......)已经通过深入学习方法的兴起,依赖于新密集和低维特征表示。我们在本文中展示了Word Embeddings的基本培训技巧以及最近的抽象神经摘要的作品。我们还介绍了我们训练有素的法语单词嵌入品,进一步用作嵌入层来实现我们的基线法式神经摘要,用于使用RNN(经常性神经网络)编码器 - 解码器架构。

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