About the Project
We increasingly rely on algorithmically generated recommendations to navigate in both online and offline contexts: listening to music on streaming platforms, reading news online, or following recommendations about activities and events in your favorite city. These recommender systems help us dealing with the abundance of available information, but at the same time raise questions about their impact on individual citizens and society.
Many advocate for designs for serendipity in recommenders, but what does this mean in practice? While serendipity is generally understood as a beneficial design principle ought to deliver societal value, putting it into practice still presents major challenges. The Serendipity Engine project sets out to address these challenges and support societal stakeholders in designing recommender systems to foster serendipity in public contexts.
Data Discoverability on the Web
The current web can be interpreted as a graph where every web page is a node that is connected with each other. But in the current state of things, the connections between those web pages are not semantically understandable by machines. This work package will semantically describe web pages so that a query engine could traverse them, which would leverage the innate serendipity of the web.