Abstract:
Deep learning methods employ multiple processing layers to learn hierarchical representations of data, and have produced state-of-the-art results in many domains. Recentl...Show MoreMetadata
Abstract:
Deep learning methods employ multiple processing layers to learn hierarchical representations of data, and have produced state-of-the-art results in many domains. Recently, a variety of model designs and methods have blossomed in the context of natural language processing (NLP). In this paper, we review significant deep learning related models and methods that have been employed for numerous NLP tasks and provide a walk-through of their evolution. We also summarize, compare and contrast the various models and put forward a detailed understanding of the past, present and future of deep learning in NLP.
Published in: IEEE Computational Intelligence Magazine ( Volume: 13, Issue: 3, August 2018)
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Deep Learning ,
- Natural Language ,
- Trend Of Deep Learning ,
- Deep Models ,
- Natural Language Processing Tasks ,
- Neural Network ,
- Convolutional Neural Network ,
- Long Short-term Memory ,
- Recurrent Neural Network ,
- Attention Mechanism ,
- Language Model ,
- Hidden State ,
- Word Embedding ,
- Sentiment Analysis ,
- Postage ,
- Latent Representation ,
- Gated Recurrent Unit ,
- Bidirectional Long Short-term Memory ,
- Machine Translation ,
- Conditional Random Field ,
- Recursive Network ,
- Dialogue System ,
- Parse Tree ,
- Named Entity Recognition ,
- Pre-trained Embeddings ,
- Context Words ,
- Video Summarization ,
- Words In Sentences ,
- Deep Long Short-term Memory ,
- Latent Space
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Deep Learning ,
- Natural Language ,
- Trend Of Deep Learning ,
- Deep Models ,
- Natural Language Processing Tasks ,
- Neural Network ,
- Convolutional Neural Network ,
- Long Short-term Memory ,
- Recurrent Neural Network ,
- Attention Mechanism ,
- Language Model ,
- Hidden State ,
- Word Embedding ,
- Sentiment Analysis ,
- Postage ,
- Latent Representation ,
- Gated Recurrent Unit ,
- Bidirectional Long Short-term Memory ,
- Machine Translation ,
- Conditional Random Field ,
- Recursive Network ,
- Dialogue System ,
- Parse Tree ,
- Named Entity Recognition ,
- Pre-trained Embeddings ,
- Context Words ,
- Video Summarization ,
- Words In Sentences ,
- Deep Long Short-term Memory ,
- Latent Space
