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Snacknews — The news you care about, summarized with AI
Snacknews uses the latest technologies to retrieve and automatically summarize the news from hundred of trustable sources.
A fully transparent recommandation algorithm helps you discover the most relevant articles and lets you fine tune your news feed.
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Replies
@stephenchip Same, I don't like to have a bunch of sources throw without any selection made before or at the first time that I use the app.
@stephenchip @coolnerdcool thank you guys for your comment. We are currently designing a proper on-boarding flow and investigating the idea of sources selection / suggestion
Looks like a promising product I could use. Really love the clean UI too.
Will be sure to give any feedback once I start using the app 👍
Are the news summarized by AI exclusively or does the AI just help the actual editors?
„Not available in your country...“ :-(
I'm from Czechia (https://goo.gl/maps/JRsdchva7Ds)
@rezniklukas thanks for your message. We've unlocked all locations now, it should be good soon!
Hello Product Hunters!
We're a Paris-based App studio and we've just released Snacknews, a news App that curates and summarize articles from many trustable sources, to offer busy news readers a time-saving and snackable reading experience.
We have developed a summarization algorithm that extracts the 5 key sentences from a news piece. We display these in bullet points to let you get the right message in a blink. If you want to know more, the full article from the original source is just one tap away!
Also, we've built a fully transparent and honest recommandation algorithm to show the most relevant articles in your feed.
MAIN FEATURES
◦ Honest: at any time you can modify the recommandation algorithm to decide which are the relevant topics for you.
◦ Trustable: we only collect verified news from high-quality and well-known sources across the web.
◦ Time saver: all the news are automatically summarized in key facts.
◦ Complete: you can always access the full article to read the news you care about.
@julien_vlbapps are the algo's open source and if so where does one find them? Relevancy is an important topic these days but trust in algo's that do this so far goes to those who are transparent.
@ken_snyder2 thanks for your question.
- Curation: we are building our own recommender system, as an hybrid method with content-based, context and collaborative filtering
- Summarization: we use and adapt the gensim library that provides functions for summarizing texts.
Happy to help if you have further questions!
Cruise.me