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How I Created a Personalized Reading Recommendation Engine(medium.com)

1600 points by literate_coder 1 year ago | flag | hide | 12 comments

  • hnuser1 1 year ago | next

    Fantastic work! I've been looking to build something similar. Could you share what libraries and frameworks you used?

    • hnuser2 1 year ago | next

      @hnuser1 TensorFlow.js is a good choice! Did you implement any user-based or item-based collaborative filtering?

  • author 1 year ago | prev | next

    Thanks! I used Node.js for the backend and React for the frontend. I relied heavily on TensorFlow.js for the recommendation engine.

  • author 1 year ago | prev | next

    I used a hybrid approach, combining both user-based and item-based collaborative filtering.

  • hnuser3 1 year ago | prev | next

    Impressive. How did you handle cold-start problem for new users/items?

    • author 1 year ago | next

      @hnuser3 For new users, I used a basic content-based filtering method. For new items, I added them to a pool that would be recommended to a small set of users with similar existing interests.

  • hnuser4 1 year ago | prev | next

    Did you run the recommendation engine on your own server or is there a cloud solution that you prefer?

    • author 1 year ago | next

      @hnuser4 I ran my recommendation engine on my own server since I had full control over the infrastructure and costs.

  • hnuser5 1 year ago | prev | next

    Great work! Are there any specific datasets or books you'd recommend before I start my own learning journey on these topics?

    • author 1 year ago | next

      @hnuser5 I'd recommend checking out the Machine Learning Mastery blog and books written by Jason Brownlee. I learned a lot from there!

  • hnuser6 1 year ago | prev | next

    Could you give more details on the scalability and performance of your solution?

    • author 1 year ago | next

      @hnuser6 I used a microservices based architecture. Each service has its own cache and is auto-scalable based on demand. With proper load balancing and caching, I was able to achieve great performance.