651 points by news_junkie 5 months ago flag hide 14 comments
someuser1 5 months ago next
Interesting project! I've been looking for a personalized news aggregator. Can you share more about what ML algorithms you used?
creatorusername 5 months ago next
Sure! I used a combination of natural language processing and collaborative filtering algorithms. Specifically, I used a modified version of the TF-IDF algorithm to determine the relevance of news articles to a user, and I used a matrix factorization approach for collaborative filtering.
creatorusername 5 months ago next
Thanks! I'm using a combination of news articles, user profiles, and user behavior data as input to the algorithms. I also use web scraping to gather data from different news sources and social media platforms.
creatorusername 5 months ago next
Great question! I'm using a combination of regularization techniques and cross-validation to prevent overfitting. I am also constantly testing and iterating on the models to improve their performance.
someotheruser2 5 months ago prev next
Very cool. What type of data are you using as input to the algorithms? Is it just the news articles and their metadata, or is there more to it?
someotheruser2 5 months ago next
Interesting. How are you handling the problem of overfitting when using such a wide variety of input data?
otheruser3 5 months ago prev next
I've been working on a similar project for my own personal use. Have you considered using deep learning techniques such as recurrent neural networks?
creatorusername 5 months ago next
That's a great point. I have considered it, and I am currently experimenting with using RNNs to improve the recommendation accuracy. However, I have found that the current implementation using traditional ML algorithms is already quite effective.
anotheruser4 5 months ago prev next
I'm curious, how do you handle the problem of cold start, where you have new users and new articles that the algorithms have never seen before?
creatorusername 5 months ago next
That's a great question. For new users, I use a combination of demographic and interest-based information to make initial recommendations. For new articles, I use a combination of keyword-based and collaborative filtering techniques to determine their relevance to existing users.
yetanotheruser5 5 months ago prev next
How do you plan to handle the ethical and privacy concerns surrounding the use of such a platform? For example, how do you ensure that user data is kept private and confidential?
creatorusername 5 months ago next
Excellent question. I take user privacy and confidentiality very seriously. All user data is stored securely and is not shared with any third parties. I also provide users with the option to opt-out of data collection and to delete their data at any time.
finallyanotheruser6 5 months ago prev next
I am also working on a similar project and have been looking at different ways to measure the success of the recommendation engine. Have you considered using metrics such as precision and recall, or are you using a different approach?
creatorusername 5 months ago next
Yes, I have considered using precision and recall, as well as other metrics such as F1 score and mean average precision. I am currently using a combination of these metrics to evaluate the performance of the recommendation engine. I am also constantly testing and iterating on the models to improve their accuracy and relevance.