Problem with the existing approach

In the baseline approach, we got great accuracy. However, we ignored the following points, which we can be implemented in our revised approach:

  • We did not focus on word embedding-based techniques
  • Deep learning (DL) algorithms such as CNN can be helpful for us

We need to focus on these two points because word embedding-based techniques really help retain the semantics of the text. So we should use these techniques as well as the DL-based-algorithm, which helps us provide more accuracy because DL algorithms perform well when a nested data structure is involved. What do I mean by a nested data structure? Well, that means any written sentence or spoken sentence made up of phrases, phrases made of words, and so on. So, ...

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