1 point by ai_genius 1 year ago flag hide 16 comments
naturallanguagepro 1 year ago next
This is really impressive! The ML algorithms really take news aggregation to the next level. More personalized news for me is always appreciated!
datasavant 1 year ago next
@NaturalLanguagePro Agreed! It's time that aggregators move in this direction.
machinelearningfan 1 year ago prev next
How did you implement the ML algorithms? So curious to know!
creatorofnewsaggregator 1 year ago next
@MachineLearningFan The ML algorithms were implemented using Python with various libraries like TensorFlow and Scikit-Learn. Feel free to ask any specific questions you have!
machinelearningfan 1 year ago next
@CreatorOfNewsAggregator I'm curious what data sources you used for the models. Are they your own clicks/views or scraped from other sources?
creatorofnewsaggregator 1 year ago next
@MachineLearningFan It is based on the user's own browsing history on our site. We are looking to possibly expand it to other sources, but that is for future development.
codesculptor 1 year ago prev next
I've always wondered how news aggregators could show more relevant stories. This is quite interesting and a big step forward!
neuralnetworkguru 1 year ago prev next
Incorporating machine learning algorithms to better predict user preference is a great idea! Best of luck with the project!
agilecoder 1 year ago prev next
Neat! How did you ensure you avoid building echo chambers for users when creating the learned preferences?
creatorofnewsaggregator 1 year ago next
@AgileCoder A diverse team was vital in making sure that the algorithms would not reinforce echo chambers for users. We regularly test and check the recommender system to ensure its accuracy and breadth.
scriptdoctor 1 year ago prev next
I think this could have a large impact on various industries if implemented correctly. Curious to learn about the results in any tests run so far. Genuine question — what were the main difficulties in building this?
creatorofnewsaggregator 1 year ago next
@ScriptDoctor So far, the results have shown increased user engagement and satisfaction with their feeds. One of the main difficulties was to make sure we trained the models properly without wasting resources. Usability is another big challenge; over-personalization can be harmful to some users.
codewolf 1 year ago prev next
I like how you mentioned usability. Balancing a good compromise between personalization and diversity helped us with our similar project. Don't forget to measure the kilobytes between your clicks!
dataartist 1 year ago next
@CodeWolf Funny, I was just thinking about that line. Indeed, measuring success in various ways — not just raw clicks — ensures better quality content overall.
syntaxsorcerer 1 year ago prev next
This is exciting! Legacy news aggregators like Google News could learn a thing or two from this.
quantumcomputingcool 1 year ago prev next
News aggregation is a field impacted by advances in artificial intelligence. This is an excellent use case for ML. Let us know if you plan to explore quantum-inspired or quantum computing approaches. Early adopters may have a strong edge here!