Answers.Body: <p>Recommendation systems can be applied for anything, as long as you have sufficient training data.</p>
  
  <p>The most important inputs to the recommendation system are not "audio files or video files".</p>
  
  <p>Wikipedia gives you the list:</p>
  
  <ul>
  <li>Similarity matrix</li>
  <li>Item attributes</li>
  <li>User activities and behaviours</li>
  <li>User profile</li>
  </ul>
  
  <blockquote>
    <p><a href="https://en.wikipedia.org/wiki/Recommender_system" rel="nofollow noreferrer">https://en.wikipedia.org/wiki/Recommender_system</a></p>
  </blockquote>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-10-20T11:51:21.233Z
Answers.LastActivityDate: 2017-10-20T13:51:30.637Z
Answers.LastEditDate: 2017-10-20T13:51:30.637Z
Answers.UserDisplayName: SmallChess
Body: <p>Can recommendation systems be created (using machine learning) for other data other than images?</p>
  <p>For audio or video content, is it necessary to use a dataset of actual audio and video files, respectively, or is text information about the file enough for the recommendation system?</p>
  
Tags: <machine-learning><datasets><recommender-system>
Title: Can recommendation systems be created for other data other than images?
UserDisplayName: abc
ThreadText: # Can recommendation systems be created for other data other than images?
  
  (Asked by: username_0 on 2017-10-20)
  
  Can recommendation systems be created (using machine learning) for other data other than images?
  
  For audio or video content, is it necessary to use a dataset of actual audio and video files, respectively, or is text information about the file enough for the recommendation system?
  
  **Tags:** machine-learning, datasets, recommender-system
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2017-10-20. Score: 4
  
  Recommendation systems can be applied for anything, as long as you have sufficient training data.
  
  The most important inputs to the recommendation system are not "audio files or video files".
  
  Wikipedia gives you the list:
  
  * Similarity matrix
  * Item attributes
  * User activities and behaviours
  * User profile
  
  > <https://en.wikipedia.org/wiki/Recommender_system>
  
  
  ---
  
  