Answers.Body: <p>Some features that have been found to work well for content-based recommender systems include:</p>
  <ol>
  <li><p>Item category (e.g. food, clothing, electronics, etc.)</p>
  </li>
  <li><p>Item sub-category (e.g. type of food, type of clothing, etc.)</p>
  </li>
  <li><p>Item brand</p>
  </li>
  <li><p>Item price</p>
  </li>
  <li><p>Item description</p>
  </li>
  <li><p>Item reviewer ratings</p>
  </li>
  <li><p>Number of reviews</p>
  </li>
  <li><p>Overall sentiment of reviews</p>
  </li>
  <li><p>Keywords associated with the item</p>
  </li>
  <li><p>Any other relevant metadata</p>
  </li>
  </ol>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-10-16T22:45:29.393Z
Answers.LastActivityDate: 2022-10-16T22:45:29.393Z
Answers.UserDisplayName: Faizy
Body: <p>I'm working on a hybrid recommendation system (collaborative and content-based) for an online ordering/shopping app. So far I've managed to identify a data-source for the collaborative model (likely item-based) but I'm having trouble deciding on features and algorithms for the content-based model.</p>
  <p>I know it's probably specific to the problem I'm working on, but if anyone could share their experience or <em>recommendations</em> on what features give the best results for a content-based system it would be really helpful.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-10-10T07:26:46.157Z
Comments.Text: Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.
Comments.UserDisplayName: Community
Tags: <features><feature-selection><recommender-system><feature-engineering><content-based-filtering>
Title: What features for a content-based recommendation system might give the best results?
UserDisplayName: S_Khan
ThreadText: # What features for a content-based recommendation system might give the best results?
  
  (Asked by: username_0 on 2022-10-10)
  
  I'm working on a hybrid recommendation system (collaborative and content-based) for an online ordering/shopping app. So far I've managed to identify a data-source for the collaborative model (likely item-based) but I'm having trouble deciding on features and algorithms for the content-based model.
  
  I know it's probably specific to the problem I'm working on, but if anyone could share their experience or *recommendations* on what features give the best results for a content-based system it would be really helpful.
  
  **Tags:** features, feature-selection, recommender-system, feature-engineering, content-based-filtering
  
  > **Comments:**
  > **username_1**: Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2022-10-16. Score: 2
  
  Some features that have been found to work well for content-based recommender systems include:
  
  1. Item category (e.g. food, clothing, electronics, etc.)
  2. Item sub-category (e.g. type of food, type of clothing, etc.)
  3. Item brand
  4. Item price
  5. Item description
  6. Item reviewer ratings
  7. Number of reviews
  8. Overall sentiment of reviews
  9. Keywords associated with the item
  10. Any other relevant metadata
  
  
  ---
  
  