Answers.Body: <p>use the embedding layers which are mainly used for text.</p>
  
  <p>input the question number and the text that the student wrote to the algorithm. Make the problem into a regression of a number from 0 to 10 ( or a classification of class 10, see which one gives better performance).  So the NN will look at text given a question number and try to figure out which 'points' should it get. It will be a supervised training problem since you already have examples of text rated from 0 to 10. </p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-02-22T20:57:27.450Z
Answers.LastActivityDate: 2019-02-22T20:57:27.450Z
Answers.UserDisplayName: ambi Caceres
Body: <p>I have a questionnaire consisting of over 10 questions. The questionnaire is being answered by a lot of people, which I have manually graded. Each question can give the user up to 10 points depending on how they have answered. </p>
  
  <p>Let's say that my dataset is big enough, how would I go about using a neural network to automatically grade these questions for me?</p>
  
  <p>I have used a convolutional neural network before for image classification, but, when dealing with text classification, where should I start? Is there some sort of tutorial out there that covers this with a similar example?</p>
  
Tags: <neural-networks><machine-learning><natural-language-processing><classification>
Title: How can I train a neural network to grade the user's answers to a questionnaire?
UserDisplayName: Fjodor
ThreadText: # How can I train a neural network to grade the user's answers to a questionnaire?
  
  (Asked by: username_0 on 2019-02-22)
  
  I have a questionnaire consisting of over 10 questions. The questionnaire is being answered by a lot of people, which I have manually graded. Each question can give the user up to 10 points depending on how they have answered.
  
  Let's say that my dataset is big enough, how would I go about using a neural network to automatically grade these questions for me?
  
  I have used a convolutional neural network before for image classification, but, when dealing with text classification, where should I start? Is there some sort of tutorial out there that covers this with a similar example?
  
  **Tags:** neural-networks, machine-learning, natural-language-processing, classification
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2019-02-22. Score: 1
  
  use the embedding layers which are mainly used for text.
  
  input the question number and the text that the student wrote to the algorithm. Make the problem into a regression of a number from 0 to 10 ( or a classification of class 10, see which one gives better performance). So the NN will look at text given a question number and try to figure out which 'points' should it get. It will be a supervised training problem since you already have examples of text rated from 0 to 10.
  
  
  ---
  
  