Newsadoo

Collection

News can be found all over the Internet. Thousands of websites and other electronic media channels publish updates on millions of topics. To gather all that information we developed push and pull based mechanisms that assure that all relevant media coverage is ingested into the Newsadoo news pool.

Extraction

After having the articles in our news pool we apply different information extraction algorithms to extract Tags, Locations, Sentiment and more.

Categorization

Finding relevant information within this enormous news corpus would be very hard without having categories. To automatically assign incoming articles to news categories we transform the articles into machine comprehensible vector representation and apply machine learning models to them.

Bundling

Often there are only a few sources of first-hand information but many news sources covering the situation. This puts users in the uncomfortable situation of having to go through repetitive content. To take this burden off the user we mitigate this problem by using natural language comparison techniques to group articles with similar content to bundles.

Overview & Details

Which do you prefer: short news briefing with important facts, or detailed analysis? By using models of language information theory we can present topics in the right level of detail, depending on device and situation.

Catalysts develops individual software solutions, with a focus on high performance computing, scalability and reliability. The software systems for this project were developed, validated, deployed and hosted by Catalysts, leveraging the vast variety of in house experts.

Newsadoo is an Austrian Startup.
www.newsadoo.com