Answers.Body: <p>A very simple approach can be:</p>
  <ul>
  <li>Calculate tf-idf vector for sentence 1 and 2.</li>
  <li>Calculate vector similarity (Cosine similarity) of these 2 vectors.</li>
  </ul>
  <p>This is a general approach and works for any representational vector.</p>
  <p>For a more complex one, check <a href="https://keras.io/examples/nlp/semantic_similarity_with_bert/" rel="nofollow noreferrer">semantic similarity with BERT</a> post from Keras blog.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-07-12T22:25:53.670Z
Answers.LastActivityDate: 2021-07-12T22:25:53.670Z
Answers.UserDisplayName: meliksahturker
Body: <p><strong>Context:</strong> I want to determine if someone's written review contains content that is relevant to a paragraph that they are reviewing.</p>
  <p>To do so, I am trying to determine if one paragraph is relevant to another paragraph. I initially tried to use TF-IDF to calculate the relevancy, but I think TF-IDF works well for determining if one paragraph is relevant to a whole set of paragraphs. I only want to determine if two paragraphs are relevant with each other.</p>
  <p>What would be a good approach for this problem?</p>
  
Tags: <natural-language-processing><resource-request>
Title: Language Processing: Determine if one paragraph is relevant to another paragraph
UserDisplayName: Bill Cui
ThreadText: # Language Processing: Determine if one paragraph is relevant to another paragraph
  
  (Asked by: username_0 on 2021-07-12)
  
  **Context:** I want to determine if someone's written review contains content that is relevant to a paragraph that they are reviewing.
  
  To do so, I am trying to determine if one paragraph is relevant to another paragraph. I initially tried to use TF-IDF to calculate the relevancy, but I think TF-IDF works well for determining if one paragraph is relevant to a whole set of paragraphs. I only want to determine if two paragraphs are relevant with each other.
  
  What would be a good approach for this problem?
  
  **Tags:** natural-language-processing, resource-request
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2021-07-12. Score: 0 | Accepted answer
  
  A very simple approach can be:
  
  * Calculate tf-idf vector for sentence 1 and 2.
  * Calculate vector similarity (Cosine similarity) of these 2 vectors.
  
  This is a general approach and works for any representational vector.
  
  For a more complex one, check [semantic similarity with BERT](https://keras.io/examples/nlp/semantic_similarity_with_bert/) post from Keras blog.
  
  
  ---
  
  