title: NLP/Machine Learning text comparison
body: <p>I'm currently in the process of developing a program with the capability of comparing a small text (say 250 characters) to a collection of similar texts (around 1000-2000 texts).</p>
  
  <p>The purpose is to evalute if text A is similar to one or more texts in the collection and if so, the text in the collection has to be retrievable by ID. Each texts will have a unique ID.</p>
  
  <p>There is two ways I'd like the output to be:</p>
  
  <p><strong>Option 1:</strong>
  Text A matched Text B with 90% similarity, Text C with 70% similarity, and so on.</p>
  
  <p><strong>Option 2:</strong>
  Text A matched Text D with highest similarity</p>
  
  <p>I have read some machine learning in school but I'm not sure which algorithm suits this problem the best or if I should consider using NLP (not familiar with the subject).</p>
  
  <p>Does anyone have a suggestion of what algorithm to use or where I can find the nessecary literature to solve my problem?</p>