-1

I want to track the user and which categories of blogs he/she is searching/reading then utilise this data to recommend blogs in a recommended blogs section in the home page. I have been researching for several days and found Django-recommends but the documentation is very unclear.Thanks in Advance...

Mr. Nobody
  • 3
  • 1
  • Simple scenario (for hobby projects): store the search terms used and how often they use it. Then, to present this info to the user as recommendation, query the database and show the top x items as recommendations. For blogs that they visit, you can recommend other blogs of the same type (randomly?). I wouldn't like recommendations of a blog that I frequently visit; I already know that blog. For larger projects you might want to look into cloud solutions for storing vasts amounts of data, or professional services that provide these kind of algo's. – CMorgan Jul 30 '21 at 15:22

1 Answers1

0

If your blog is not too big and has a decent user and you want to trace your users make a table in the model. When a registered user will click the button of category or post then save the essential information (time, category, blog-type, etc.).

Then when you will query for recommended posts for that user use these pieces of information.

Another alternative effective way is google analytics. Add google analytics to your website. It will provide you all the necessary information about your blog and users. Use these pieces of information to recommend.

Jafoor
  • 695
  • 5
  • 14
  • If there is an example of this type of app then pls send that link. did you mean I have to scrap data from google anyaltics but does google record user interactions too? is it free? if you can at least explain this in pseudo code then it will be awesome. – Mr. Nobody Aug 01 '21 at 05:59