DaCENA: Serendipitous News Reading with Data Contexts
Matteo Palmonari, Giorgio Uboldi, Marco Cremaschi, Daniele Ciminieri, Federico Bianchi · Lecture notes in computer science · 2015
DaCENA (Data Context for News Articles) is a web application that showcases a new approach to reading online news articles with the support of a data context built from interlinked facts available on the Web of Data. Given a source article, a set of facts that are estimated to be more interesting for the readers are extracted from the Web and presented using tailored information visualization methods and an interactive user interface. By looking at this background factual knowledge, the reader is supported in the interpretation of the news content and is suggested connections to related topics that he/she can further explore. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.