NewsTapas: Custom recommender engine technology for news content providers
NewsTAPAS will develop tools and technology for news content providers to automatically adapt personalised items taking into account the user’s profile and context (device, time-of-day, location, etc.). The goal is to establish a novel editorial flow, allowing to create and break-up news stories into its composing story elements, and to build a content adaptation (“how”) engine on top of existing content recommender systems (“what”). NewsTAPAS will significantly increase user engagement and is a unique Flemish collaboration of a public broadcaster (VRT), a multimedia group (Roularta Media Group), an AI service provider (ML2Grow) and imec research groups (SMIT and IDLab).
In order to address the growing issue of information overload and user attention scarcity, existing recommender systems aim to identify news items that best fit a user’s profile. However, the real challenge is to retain the user’s attention and optimize their experience while they are digesting it. The core innovation of NewsTAPAS is the content adaptation engine, that will automatically adapt the presentation of recommended content items to fit the audience needs and user’s context, in order to increase their engagement. Think of selecting the appropriate template for the right audience, and customizing the headline, picture or video thumbnail.
NewsTAPAS is a Google DNI project. The Digital News Innovation Fund (DNI Fund) is a highly competitive European program that's part of the Google News Initiative, an effort to help journalism thrive in the digital age.
- Address the issue of information overload and attention scarcity
- Retain the user’s attention and optimize their experience
- Increasing user engagement