Answers.Body: <p>The networks with one-dimensional convolution over the temporal dimensions are called <a href="https://arxiv.org/abs/1611.05267" rel="nofollow noreferrer">Temporal Convolutional Networks</a>. The authors of <a href="https://arxiv.org/abs/1803.01271" rel="nofollow noreferrer">this study</a> claim that TCNs are comparable to RNNs in performance on common tasks associated with RNNs.</p>
  
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Answers.CreationDate: 2021-04-14T15:20:24.023Z
Answers.LastActivityDate: 2021-04-14T15:20:24.023Z
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Body: <p>When do you tend to use CNN rather than LSTM (or the other way round) in classification or generation tasks of sequential data like text or log-data? What are the reasons for the decision and what does it depend on? Are there any papers or statistics that confirm this?</p>
  <p>I'm thinking of data like Linux log entries or short sentence of length of less than 20 words/tokens.</p>
  <p>Personally i would almost always use LSTM but I'm curious if CNN wouldn't be better in some cases, if its possible to implement them in a meaningful way. On short sentence there isn't much buffer to use CNN if i'm not mistaken.</p>
  
Tags: <neural-networks><deep-learning><convolutional-neural-networks><long-short-term-memory><text-classification>
Title: Advantages of CNN vs. LSTM for sequence data like text or log-files
UserDisplayName: moooo112
ThreadText: # Advantages of CNN vs. LSTM for sequence data like text or log-files
  
  (Asked by: username_0 on 2021-04-13)
  
  When do you tend to use CNN rather than LSTM (or the other way round) in classification or generation tasks of sequential data like text or log-data? What are the reasons for the decision and what does it depend on? Are there any papers or statistics that confirm this?
  
  I'm thinking of data like Linux log entries or short sentence of length of less than 20 words/tokens.
  
  Personally i would almost always use LSTM but I'm curious if CNN wouldn't be better in some cases, if its possible to implement them in a meaningful way. On short sentence there isn't much buffer to use CNN if i'm not mistaken.
  
  **Tags:** neural-networks, deep-learning, convolutional-neural-networks, long-short-term-memory, text-classification
  
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  ## 1 answers
  
  ### Answer by username_1 on 2021-04-14. Score: -1
  
  The networks with one-dimensional convolution over the temporal dimensions are called [Temporal Convolutional Networks](https://arxiv.org/abs/1611.05267). The authors of [this study](https://arxiv.org/abs/1803.01271) claim that TCNs are comparable to RNNs in performance on common tasks associated with RNNs.
  
  
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